What does the Post COVID-19 Landscape in business look like?

How will the Post COVID-19 pandemic landscape in business be changed? Are we headed to a future like the Jetsons or one like Mad Max? Companies who once feared remote workers are waking up to the benefits of this work/life balance. Others are in panic mode because “we’ve always done it this way” no longer applies.

As a Data Science company, we are always looking ahead. One thing we get asked about is what should business be doing now to prepare for the world in the new normal. At our first in-person lunch meeting Post COVID-19 pandemic, we came to the conclusion the two book-ends are: Jetsons or Mad Max.”

Here are some of our thoughts:

The Post COVID-19 Business Landscape

We believe the major change is how customers now interact with companies. We have, because of the pandemic shown that companies can actually do just fine working from home, can deliver good like groceries, food, and even luxury items without the in-person experience, and that companies can do a better job using technology to deliver what the customer wants, when the customer wants it.

This is pandora’s box. We can’t go back. Because we had to do this to survive, now we have to continue to do it as part of our business model. However, what most companies built in haste, isn’t scalable. It is now time to rethink how we use the data we have (and the data we can get) to build a scalable solution that gives us insight into what customers want, and gives the customers what they desire–better access.

Interestingly enough, when going back through our past project history, we realize we have been building solutions for just this problem for years. Take for example the persona model we built for Omaha Public Power District (OPPD). It is a great example of how to use data for greater impact.

For OPPD, one of the few publically owned utilities in the entire country, our predictive model allowed them to understand which product or service each household had the highest chance to purchase, and then give that insight to their sales and marketing teams. This meant that:

  1. Their customer service agents now had access to which products to recommend when they called in.
  2. Their sales team knew which households were most likely to want each product, and
  3. Their marketing team knew which product to market to each household.

Predictive modeling like this allows companies to “hit” more than “miss”. If your able to be more effective, even by a small margin, you may edge out your competitor. Tell that to Jacob Kiplimo who was on pace to set the world record for a 43:00 15km run. Kiplimo raised his arms to celebrate before crossing the finish line. It was then that Kibiwott Kandie passed him and finished in 42:59 and was the first to break the record instead.

Understanding how to start with data-driven decisions can be tough. Lucky for you, there is a company that can help you get this kind of insight, and teach you how to do it. Contact Us today and we’ll be happy to help ensure you hit the ground running post-COVID.

How CAN Takes a Different Approach

At Contemporary Analysis (CAN), we take a completely new approach to helping companies and organizations get more out of the information they have access to. At our core is the idea that businesses should be working smart and hard.  At CAN, we are different because we always keep the human element, actionable impact, and added value at the forefront of our development process.

We start the entire process with keeping the human element in mind. Everyone has gone through the frustrating process of being passed off from one person (if you’re lucky enough to reach a real human) to the next throughout a customer service or sales process. In most of these situations, half the time speaking with a new person is catching him or her up on things you have already said to other members of their organization.
At CAN, we understand the importance of having one contact throughout the entire process. This contact, known as a Navigator, takes the time to understand your specific business and helps you distill problems with big impact solutions. Navigators understand the majority of managers and executives don’t have the time to learn about predictive analytics. Navigators take the time and effort to understand the problem or issue from the end user’s point of view and then strategize to reverse engineer an efficient solution. It is our job to couple your expert knowledge and historical data to give you a solution with impact.
At CAN, we understand businesses outsource services for added value. The value of using predictive analytics is only as great as the actions and changes made with the information provided. You could have a GPS system in your car, but if you never turn it on, it doesn’t do you any good. From step one in our customer process, we work on finding helpful insights into areas in which you can TAKE ACTION or MAKE CHANGE, not just look at the report and think “Hmm, that’s interesting.” If the information we provide doesn’t induce change on at least some level, we didn’t properly do our job.
At CAN, the solutions we provide make sense financially. We use predictive analytics to answer questions in about 30 days. Think about that for a second. In just 30 days you could have an analytical model which, while not being perfect, will allow you to make much more informed decisions. Whether it’s having a better understanding of up-sell, cross-sell, or customer loyalty. It is important to remember, the goal of predictive analytics is to be LESS WRONG, and models continually become less wrong by using current information to test and re-test.
Compare 30 days with CAN to the alternatives – doing nothing or creating an in-house predictive analytics department. In smaller companies, the alternative to CAN is to do nothing. Smaller companies don’t have the resources to create in-house predictive analytics, but have a lot of the same issues as large companies.
The other alternative is in-house analytics. I believe in-house predictive analytics departments are something every large company should invest in. Properly managed and financed in-house departments can change organizations in ways never thought possible, in ways which only the future will show us. No longer would justifications for decisions be based on gut instinct, or worse yet, “because that’s how we’ve always done it.” This business is your passion, and nothing proves a point faster than quantitative justification. However, what if you’re not a large company?
In-house departments require management, direction, and resources. A company looking to develop the smallest possible in-house predictive analytics department will pay for the following:

  • Find and hire a highly sought after Ph.D. or Masters at a cost of 75-150k.
    • Add half the salary again for employee benefits, taxes (FIFA, FICA, etc.), office space, physical equipment, and HR resources.
  • Purchase a Tableau, SAS, or SPSS license costing 10’s of thousands of dollars for just one year

This cost of 175-250k is just the initial investment. You haven’t solved one problem yet. Taking into account the months of required training and corporate acclimation before any useful insights can be made by this new hire, it can be 12 to 18 months before you have a solution to just one of your smallest problems. 30 days and a cost of at least a zero less sounds much better to me.
Like I said before, I would encourage all large companies to take the plunge into predictive analytics. Even with well developed predictive analytics solutions there is a high possibility the department would suffer the same downfall as some IT departments, the disconnect between who designs or provides the technical knowledge and who actually uses it on a day to day basis.
At CAN, we take your expert knowledge and use your data to provide valuable insights you never thought possible. Throughout the entire process, we never lose track of the importance of the human element. Whether you’re a large company with an in-house analytics department or smaller business with no means for self analysis, we care about your business and can give you value in the form of information from which actions can be taken.

Managing Smart People: Leaders and Experts

CAN’s success depends on our ability to provide great jobs to innovative and creative professionals. However, managing these highly intelligent and creative people can be challenging.  Smart people want clear career paths, frequent meaningful promotions, and competent managers.  If smart people perceive a position lacking, they quickly lose motivation.  For example, smart people quickly lose respect for a manager they perceive as being incompetent or  less intelligent.  CAN has tried to address the challenges of hiring smart people.
First, we have limited the number of positions that are not core to the business. If possible we have outsourced any position that is not sales or operations. Essentially we have outsourced for quality not price. This has created an organization were almost every position has a clear career path. This has allowed CAN to focus on building in-depth training programs that allow us to develop our people so that they can earn frequent and meaningful promotions. (more…)

Tadd and Jefferson go Mining for Data in Wyoming

CAN is helping one of our clients improve their asset management strategy, by building predictive models to determine when heavy equipment is most likely to fail.
CAN’s asset management models will allow our client save hundreds of thousands of dollars each year, by converting emergency repairs into scheduled maintenance.  Imagine the money and time that can be saved if repairs can be preemptively made in several hours instead of the weeks or months it takes to make repairs in the field.
While we could have developed the model from our offices in the Old Market, we needed to make sure that we understood the conditions on the ground. Jefferson and Tadd decided to take a trip to Wyoming and spend a week learning about the machines and interviewing the experts that use the equipment on a daily basis.
Their goal was to make sure that we had political support from the people that were going to use our models, and that we could build balanced models that combine data, theory and math.  The following are some of the photos from their trip.  I hope you enjoy.

Mining for Data

We might push paper for a living, but we love to get our hands dirty to build beautiful models and to understand your business! Please contact us to learn how we can help you.

Why I became a Data Scientist at Contemporary Analysis

My name is Branden Collingsworth. I interned at Contemporary Analysis this summer, and joined the team full-time January 2nd, 2012 as a data scientist.  As a data scientist I use tools from econometrics, statistics, operations research, and data mining to solve our client’s business problems.
Why did I decide to work at Contemporary Analysis?
While working on my undergraduate degree in economics and my MBA, I really enjoyed learning about the tools available for the kind of analysis we do here at CAN.  While data science is a growing field, there are relatively few data science companies.  More importantly, many of CAN’s competitors don’t have the same emphasis on business that we have.  CAN approaches clients to help improve their business, not just to show off fancy statistical techniques. That business-centered approach is really refreshing in an industry that is easily bogged down in esoteric discussions of complex methodology. I’m passionate about the focus on practical result that can be easily implemented to make a big impact.
What do I like most about working at CAN?
Because our clients represent a wide range industries and sizes, every project is unique. I am really excited by the opportunity to learn something new about our clients. When we can look at a data set and can discover new knowledge like which customers are most loyal, what causes employee turnover, how economic forces outside the business influence revenue, or where is the best physical location for a business, we are learning something new about our clients’ businesses, something that is valuable and has real business consequences. We can have big impact on our client’s business which makes for very satisfying work.
What do I like most about being a data scientist?
Data science a really interesting and challenging field. It’s such a new field, there is a lot to learn and the methods are changing and evolving. New techniques are becoming more and more relevant all of the time. Working in this field requires knowledge and passion about such a wide range of topics: psychology and human behavior, economics, computer science, marketing, statistics, operations research, decision science, and even linguistics. I love the challenges that come with working on these kinds problems. There is never a dull day.
What are you most excited about for your future at CAN?
I think as more businesses begin to understand what we can do for them, we’ll get more and more interesting projects. I like to see people make informed and well thought out decisions, and that is what CAN is all about. I think we are on the vanguard of a big change in the way people think about making business decisions. Now that the data is increasingly available people can either use it or ignore it. Those who put information to its best use will have a significant advantage over everyone else. It’s inevitable, and I want to be a part of it.
I am excited to join the Contemporary Analysis team, and helping CAN’s clients work smart.  You might also enjoy Predictive Analytics and the Evolution of Business Intelligence and the Future Belongs to Data Scientists.

How to Build a Small Business Call Center

Everyday, the CAN team interacts with clients, mentors, and friends who are leaders in their fields, and we started this series to share their expertise.
As a part of our research I interviewed Nathan Waite.  Nathan is the National Sales Director for SEMCAT Quoting Software headquartered in Lincoln, NE.  I found his advice helpful and I wanted to share it.
Hire Competitive & Passionate People:  When screening candidates, Nathan ranks competitiveness as the most important criteria for hiring new salespeople.  He has found that salespeople with competitive spirits are energized by quotas instead of being exacerbated by them.  However, he is quick to point out that a competitive spirit needs to be tempted by emotional intelligence.  Nathan doesn’t tolerate any drama on his team and salespeople need to be able to stay in the game even when they are down.  The third criteria is that people have to be passionate about SEMCAT’s products, since they are going to spend hour after hour talking about SEMCAT’s product.  However, passion about the product is different and more important than technical understanding.  Nathan has found that if people are passionate and competitive they can learn exactly how everything works.
Leader Planks not Leader Boards:  Competitive and passionate people love to know their score and the score of the company so Nathan uses call center metrics to keep his people motivated.  However, what used to be a Leader Board is now a Leader Plank.  Too many call center metrics are difficult to keep track of and distracted people instead of focused them.  Instead, The Leader Plank contains 5 call center metrics, current marketing yield, phone minutes per month, total sales per month, evaluations, and accolades.  The following is an example of SEMCAT”s Sales LeaderPlank:

Call Center Metrics LeaderPlank

3000 Minutes per Month: A salesperson’s job is to talk to as many customers as much as possible.  However, how much time is enough time.  For people that work a 9-hour day, there are 9,600 minutes of work per month, but how much of that can be spent on the phone with clients?  According to Nathan the answer is 3,000 or 31% of a 9am to 5pm Monday thru Friday work schedule.  At this rate salespeople will feel like they spend all of their time on the phone, but will also avoid burnout.
Power 50’s:  To help each sales person achieve their 3,000 minutes a month, Nathan employs what he calls “Power 50’s”.  Each Power 50 is 50 minutes long.  This is the longest an average salesperson can spend on the phone while being productive and without burning out.  He encourages his salespeople to block out 3 to 4 Power 50’s each day, and use that time call on clients.  They are supposed to treat that time like an appointment and focus all of their efforts on making phone calls.  They can return to calls, send emails and schedule other meetings around their Power 50’s.
Separate Offices:  While big companies can get away with putting a lot of salespeople into open floor call centers, Nathan recommends that if you have less than 12 people per room it is more cost effective to build individual offices.  The reason is because people are too polite.  He has found that salespeople will take turns when making phone calls or listen to other people calls and take notes.  This is especially true if their are 2 or 3 people in an office.  Basically if you have 2 salespeople in an office together, you would be better off just having one.  So if you are going to spend the money building a call center, hiring, equipping and training salespeople, maximize your investment, put them in their own office.  If salespeople have to share an office you can help them focus by giving them full headsets instead of just single ear headsets.
Phones, Headsets and Providers:  Call center telephony is an interesting industry.  There are so many options, little marketing, and no clear leaders.  Growing up without a telephone monopoly or a landline selecting a phone provider and hardware has been borderline infuriating.  I have struggled with the fact that desktop phone lacking any thought to user experience, with a “cutting edge” 16-bit color screen, that can only make voice calls can be more expensive than my computer, while Skype can make free video calls.  Nathan recommended using a Voice over IP (VoIP) system if you have an internet connection with significant upload and download speeds.  For example, CAN has 5mb upload and download for 30 people.  The VoIP provider that Nathan recommends is OnSip.  His plan for phone is simple.  He gets the phones for as cheaply as possible, and invests in great headsets.  For phones he recommends either the Polycom 430 (1 or 2 line, no backlight) or 550 (4+ lines, backlight), because they are simple and good enough to get the job done.  He recommends buying phones from eBay, because he can get them at about a 50% discount from retail and it doesn’t matter if they are used.  He uses the 50% savings to purchase each salesperson a Plantronics SupraPlus CS361N Noise-Cancelling Wireless Headsets.  Personally he uses a Plantronics CS 55 w/ Plantronics HL10, because he prefers to have one ear free in case of an emergency.
Click-to-Dial:  I asked Nathan if he had any recommendation and his only advice was to use a CRM with a Click-to-Dial feature.  This allows people to stay focused on communicating with clients instead of dialing.  In Nathan’s opinion this is the most important feature of his CRM, and it helps his salespeople meet the requirement of being on the phone for 3000 minutes per month.
Learn about building a dashboard for your call center, download “Dashboards: Take a closer look at your data.”

Take your call center even further. Learn how using our eBook, Predictive Analytics: The Future of Business Intelligence.

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Why Customer Segmentation Will Improve Your Marketing

I have been married for almost 10 years. I have gotten good at buying gifts, even clothes. I can match blouses and jewelry, dresses and belts, shoes and jeans. My secret? I look at the mannequins. Mannequins were designed to attract your attention in a store window and to lure you into the store. Then inside, they are designed to show you some of the combinations you could make with their clothes. Essentially they are designed to get you to buy more than one thing. This is perfect for guys. All we have to do is point to the mannequin and ask a store sales person where we can find those certain pieces of clothing.  We can buy the mannequin lock stock and barrel and end up with a complete outfit for our brides.
This is actually what I do when I do marketing for companies. Marketing comes in two forms. Marketing to your current clients and marketing to people who aren’t your current clients. I view each as a completely different problem while most marketing companies do not. They have only have one mannequin with the same clothes for every store. Children’s clothes, women’s clothes, men’s clothes, all the same mannequin.
Unfortunately most of the marketing plans I see are all the same. The commercials are different but the plan is the same. They do direct mail, email, print campaign, radio, and if they have the budget, TV ads. Their view is that all people are potential clients which as you who follow the blog know, is not true.  The problem is that they have no idea who their target audience is, and how to market to them. They found a campaign that reaches a lot of people and they sell you that one. It may have different clothes, but it is the same mannequin. It is essential to use customer segmentation to improve marketing.
This is critical to understand. Gone are the days when people walk down a street with stores on it, see a mannequin, and make the decision to go inside. Now, people browse their favorite stores online and are more loyal to store brands like Gap, Old Navy, JC Penny’s, Younkers, and Von Mauer. We have to get a new mannequin.
Mannequins, models, are going through a huge makeover right now.  In fact, if you do a job search for entry-level marketing positions, they are looking for things like statistics, modeling, and analytics in your background. What they are struggling to come to understand is the idea of marketing to one person at a time. Marketing now needs individualized messaging.
I don’t have to go to far back to find when this was still science fiction. Minority Report (2002) shows a seen where character John Anderton is walking through the mall and cameras recognize, data base search, and present relevant ads, based on his buying history. To see a version of this now, just go to iTunes. Any song I buy will create 5 suggestions of other songs I might like, based on my buying history, songs with similar tempos, themes, or by the same artist. With a predictive analytics company like ours, we can do the same thing for your product.
First you have to understand something about how we view marketing. This is the key philosophy that makes us different. Marketing is using a different medium to get in front of your target audience for the sole purpose of selling to them. Selling to them. The sole purpose.  EVERYTHING else is branding. Branding is fine. We do a lot of branding. We just don’t call it marketing. That key aspect alone will forever change the way you do marketing. When you use it as a sales tool, you will no longer accept marketing with no measurement of who looks at it, how it is crafted, and where it is put. It will focus your marketing on only the people who have an actual chance to buy from you in the marketing cycle. This does not include: people who might buy, people you think need to be introduced to your product, or someone who might have a need someday. What marketing with the intent to sell does is only spend your time and money on the people who are ready to buy now.
How do we do this? We use math and econometrics to understand the buying process. What causes people to think of buying a product like yours? What series of events leads to needing a product like yours? Who are the people in a company that make the decision to buy a product like yours? These are important things to understand in the process. Don’t market to someone who doesn’t need what you are selling, isn’t high enough up in a company to make any kind of decision, or hasn’t experienced any kind of problem that your product would fix. It wastes time. Why would you ever market a phone system to a sales person. They can’t buy it. Why would you ever market a copy machine to a company of 4 people. They can’t afford it.
I have heard the argument that you need to be in front of those people now so they think of you when he problem arises. Valid argument. However, because of the new view of marketing I just gave you, that states that marketing is used as a sales tool to find people who are ready to buy now, you can see that this is branding. Branding is necessary, we do branding; however, if you have a company like us who markets you correctly, i.e. to the right people, at the right company, at the right time, you don’t even need to do that.
Example.  Name someone who makes shingles.  Not someone who installs them, someone who makes them. Why don’t you know? Shingles protect everything in your home and are the first thing damaged in a storm. If you own a house, shouldn’t you know who the best, worst, and middle of the road companies are in the shingle business? The reason you don’t need to know, is that you don’t need shingles. When the time comes and you need shingles, you will do your research and find a company that installs the type of shingle you want on your home.
It’s the same for business. People don’t really need to know about your product until they start doing research about your product. Key point: Up until now, you had to guess when companies were going to need you and you had to brand so that people remembered you when that time came. Now, with analytics, we can predict when to contact companies because we can predict when they should be beginning research on products similar to yours.
Think about this — how can a marketing company know where to put your ads either on TV, radio, direct mail, email campaigns,and social media without knowing what causes someone to buy your product. Its time to start marketing differently. Instead of putting mannequins in the window, lets know the person that is walking down the street. Lets advertise to them when they need us, want us, and can afford us, and save our money on tire kickers, time wasters, and spectators.  Its time to spend your hard-earned marketing budget on the people who we need to talk too. Its time to work smart.

Job Board: Contemporary Analysis Navigator

Contemporary Analysis is a global data science company based in Omaha, NE that provide predictive analytics to multiple Fortune 500 companies and small businesses in the United States, Europe and Asia.  Contemporary Analysis is focused on making analytics accessible to companies of all sizes and industries, and offers standard products and professional services.
Contemporary Analysis (CAN) Navigators are the core of CAN’s client experience.  They are responsible for helping customers achieve their business goals by helping them discover, understand and use CAN’s business systems.  This is the perfect position for someone that loves to continually learn and teach others.  Navigators are responsible for learning about client’s businesses and their goals, researching and helping them develop and implement a plan to help them Work Smart.  They must be experts in both the technology and customer service.
Primary Responsibilities:
Introduce: CAN Navigators are responsible for introducing clients to CAN to determine if they have a need, willingness and resources to purchase CAN’s systems.  This includes handling incoming clients from CAN’s website and referral program, and also contacting sales leads qualified with CAN’s Tracker system.
Discover: Once a client has been introduced to CAN, and has expressed the need, willingness, and resources CAN Navigators will train to be experts at data science and business so that they can work with clients to understand their business and their business goals.  Clients should be confident that their Navigator has a good understanding of their business.  If a Navigator is not sure that they fully understand a client’s business, their business goals, or the right solution they will research until they understand more.
Create: After the Discover stage, Navigators will work with Client to create a plan to help them achieve their business goals.  This will include discussing CAN’s systems, as well as third party products and services.  The purpose of this step is to collaborate with clients to create a timeline and action plan to work smart.
Work: After the Create stage, Navigators will work with Clients to setup and understand CAN’s systems in their businesses, and then work with each client to help them achieve their business goals.
Relevant Experience and Education

  • Minimum Education: Bachelor’s Degree from an accredited institution, with a degree in business or relevant work experience.
  • Able to maintain focus in a high charged environment and manage competing priorities.  This includes experience managing multiple projects simultaneously against tight deadlines.
  • Experience solving business issues with the consultative application of advanced analytics and/or information technology.
  • Strong presentation and client management skills, up to the Executive level.  This includes being able to explain highly detailed and technical subject matter to non-technical audience, and being able to present and sell analytical concepts to clients.
  • Experience delivering insight to internal or external clients by building on a technical foundation that includes a conceptual understanding of modeling techniques and a basic grasp of statistics.  Ability to build analytical applications to solve a practical problem, in an on the spot high-pressure situation.
  • Experience in project management and managing a team to meet a deadline, manage client expectations, and maximize client satisfaction relative to solution profitability.
  • Functional experience in one or more of the following areas: selling analytic services, project management, analytic product development, pre-sales, implementation, account management
  • Technical foundation to include one or more of the following areas: Bayesian statistics, multiple regression analysis, econometric modeling

If you are interested in learning more and applying contact Grant Stanley by phone at 866-963-6941 #801 or connect with him on LinkedIn.  Please have your LinkedIn profile up to date before applying.

Data Scientists are the Future

Data scientists help people create knowledge from data, including sometimes million of gigabytes of data.  An example is iTunes using the number of songs and length of each song on a CD to find the name of the CD, the artist, and the titles for each song.  To data scientists, tracks on a CD are not music, but data.

Until the turn of the century, someone’s knowledge was limited by their access to a library or university.  Now, because of the increasing power and storage capacity of computers, and the increase in data being published, someone’s knowledge is limited by their ability to process data.  For example, for $600 you can  buy a hard drive capable of storing all the music in the world. (more…)

Contemporary Analysis Job Board: Data Scientist

Contemporary Analysis (CAN) is a global data science company based in Omaha, NE that provide predictive analytics to multiple Fortune 500 companies and small businesses in the United States, Europe and Asia.  CAN is focused on making analytics accessible to companies of all sizes and industries, and offers standard products and professional services.
The purpose of this position to help expand our professional services team.  CAN’s professional services team is responsible for developing solutions for CAN’s largest and most unique clients including Fortune 500 and Global Fortune 50 companies.  The by-products from the team’s professional services are used to create new and enhance existing CAN products.
Each Data Scientist is responsible for working with a CAN Sales Executive to understand each client’s business, define projects to help clients achieve their business objectives, use data science to develop solutions, and present results as a written report and presentation.  Data Scientists must be familiar enough with statistics and computer science to develop creative solutions, and have the written and verbal skills to develop compelling reports and presentations.
The Data Scientist will be responsible for:

  1. Working with the Sales Executive, the Data Scientist will work at all executive levels to help design solutions that will meet the needs of the client.  To be able to design creative solutions that go beyond simple client feature requests will require Data Scientists to have an advanced familiarity with modeling, mathematics and statistics.  Also, during the discovery phase the Data Scientist will coordinate with the COO and Sales Executive to develop project budgets.
  2. During the implementation phase, the Data Scientist will work with other CAN Data Scientists and vendors to implement the Analytical Blueprint, and monitor client results, and adjust the Analytical Blueprint to optimize the client results and experience.  Since CAN offers data science solutions as a service, implementation can last from a month to several years.  This creates a unique project management scenario that requires continuous monitoring to ensure that the project does not fall behind.
  3. The Data Scientist working with the Sales Executive will maintain a positive relationship with the client, ensure ongoing deliverables are met, and assess any future need for CAN’s services.  In some cases the Data Scientist will need to record best practices from the project, or write specific business issue case studies.


  1. Minimum Education:  Bachelor’s Degree from an accredited institution.
  2. Able to maintain focus in highly-charged environments and manage competing priorities.  This includes experience managing multiple projects simultaneously against tight deadlines
  3. Experience solving business issues with the consultative application of advanced analytics and/or information technology
  4. Strong presentation and client management skills – up to the highest executive level.  This includes being able to explain highly detailed and technical subject matter to non-technical audience, and being able to present and sell analytical concepts to clients
  5. Experience delivering insight to internal or external clients by building on a technical foundation that includes a conceptual understanding of modeling techniques and a basic grasp of statistics.   Ability to use analytical applications to solve a practical problem, in an on the spot high-pressure situation
  6. Experience in project management and managing a team to meet a deadline, manage client expectations, and maximize client satisfaction relative to solution profitability
  7. Functional experience in one or more of the following areas, selling analytic services, project management, data science product development, pre-sales, technology implementation, and/or account management
  8. Technical foundation including one or more of the following areas, Bayesian statistics, multiple regression analysis, and/or econometric modeling is preferred but not required.
If you are interested in learning more and applying contact Grant Stanley by phone at 866-963-6941 #801 or connect with him on LinkedIn.  Please have your LinkedIn profile up to date before applying.
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