Client: Client produces a state of the art data analysis and presentation software program used in the biotechnology space.

Project Focus: It has used USB “Dongles” to provide single user software licenses, and needs assistance in:

(1) analyzing data to determine whether USB drives may be differentiated to introduce and support a a time-based upgrade policy. Determine the feasibility of time-based upgrade policy and make recommendations for how this could be implemented

(2) recommendations for marking and identifying USB drives going forward to enhance customer support, rapid upgrades, and internal tracking.

Expertise required: 

• Demonstrated ability to deliver targeted BI data analysis and visualization 
• Understanding of software licensing and sales 
• 5+ years experience with data pre-processing and analysis in R or similar 

Data Sources & Format: 

• 3 column CSV file which will require some pre-processing to align dates, invoice numbers, and USB ID's 
• Detailed documentation of version authentication history and proposed plan moving forward.

 A summary of our business

W2O Group is a top-ranked independent network of complementary technology-enabled marketing and communications firms. We are comprised of four separate companies, 12 offices and about 500 people. Today, the company generates nearly $100 million in revenue annually and serves some of the world’s leading companies and brands.

 The problem that we are trying to solve / the questions that need to be answered:

W2O Group is performing an in-depth summary of online conversations surrounding a pharmaceutical brand [brand] and its competitors. The purpose of the analysis is to develop an understanding of the relevant online conversation, both pre- and post-FDA approval of [competitor 1] and to identify stakeholders and discover discussion patterns within the set of conversations. This in-depth “competitive analysis” will focus primarily on conversations from patients and caregivers.

From this online listening data feed, the expert will be able to deliver on the following questions/challenges:

• What percent of these posts that mention [the brand] are relevant?
• In what channels are the conversations happening on [the brand]? The data will include posts from Twitter, blogs, forums, online news, and open Facebook groups
• What are the types of posts being written (quantify) about [the brand]?
• Do the stakeholders compare [the brand] and its competitors in the article or post? If so, with whom?
• What is the sentiment of these posts with respect to [the brand]? Is there a change in sentiment with time?
• What are the topics most/least talked about with respect to [the brand]?
• What other treatment(s) are mentioned in addition to [the brand] within the post? 

Please note that the data needs to be coded/analyzed manually and not through any kind of NLP (natural language processing) software.  

The kind of expertise we require:

• BA/BS required
• Strong analytical skills with the ability to collect, organize, analyze, and disseminate significant amounts of information with attention to detail and accuracy
• Social Listening Analysis experience preferred
• Healthcare experience preferred
• Strong knowledge of Microsoft Office Applications (specifically Excel, PowerPoint, and Word)
• Strong communication skills across platforms, such as email, phone, and video conference

The data sources at your disposal and their formats (Pricing data in CSV format, etc.):

• The fixed feed of conversation data (social and traditional media specifically: Twitter, News, Forums, and Blogs) in Microsoft Excel
• A guideline to reading and interpreting the conversation data

 Format of the final deliverable (algorithm, dashboard, web application, advisory service, etc.):

W2O Group would like the completed Excel document and all corresponding worksheets along with a bullet-point summary on the findings. This summary can be a separate tab within the Excel document or a number of PowerPoint slides, as long as they answer the aforementioned business questions.

 Sample data file:

Please see the file “Experfy - sample coding worksheet 111115.xlsx” within the project files.

 Final deliverable method of deployment (i.e. cloud, FTP, email, etc.):

A delivery via email will suffice.

Please review project timeline and deadline attached. We are looking for this project to be completed in 5 business days from green light.

We are an online entertainment and media company that sells memberships to our content collection online. (i.e. Netflix)

Our goal is to increase sales by improving the algorithm that determines the order of thumbs that our lander shows.  Additional goal is to come up with a automated system to introduce new thumbs to the lander.

Our lander: http://cdn.teamskeetimages.com/template_tour.jpg 

Our join page: http://cdn.teamskeetimages.com/template_join.jpg

Sales Funnel:  

A. Click on advertisement links / type in

B. Tour page / click on thumbs

C. Click on join page (Fill out join page)

D. Biller page (fill out and submit)

E. Approval Page

Data we collect:

1.  Traffic / impressions

2.  Sales 

3.  CTR (Click Thru Ratio)

4.  Time 

5.  Spot (location of thumb)

6.  Type of device (desktop or mobile)

Our current tour algorithm is:

75% x Average daily joins + (25% x CTR x added factor)

Where added factor is a number that we increment 0.02 every 3 thumbs.

Example

1.00 for thumbs 1 to 3

1.02 for thumbs 4 to 6

1.04 for thumbs 7 to 9

Misc Points to Consider:

A.  Our surfers come from all across the world (English speaking countries is our focus) and thru all different sites (including Tube sites, Review sites, etc) - The quality of varies greatly from region to region to type of sites the surfers are coming from.

B.  Added Factor is used in our algorithm with the thought that the lower the thumb on the list - the less chance it has of being seen 

C.  Custom thumbs - one of the most important points.  We add new thumbs on a daily basis to the system.  On the above image, we use Thumb 5 / 10 / 15 as custom thumbs, we let these spots get traffic for a few days to give it a push, then release it to the tour and let the thumb end up where it may. One of the secondary goals is to have an optimal, automated strategy to test these custom thumbs.

D.  Our landers can vary how many thumbs are shown depending on how big the consumer monitor is - lowest being 2 - highest being 6.

You will be working to clean our historical (end of day) financial dataset (this contains date, symbolid, symbol, open, high, low, close, and volume – 8 fields in total). This data set contains about 17M records. Most of the records are clean; however, some records contain NULLs, 0’s or invalid values. Also, there are some duplicate records. See attached sample_data.csv.

This project will involve reviewing the full CSV of this data, and extracting supplemental data from Xignite for comparison. You will also gather (free) end of day data from Yahoo Finance and Google Finance as an additional comparison. Then, the datasets must be compared. The goal is to create a single most accurate dataset, which is likely a combination of the sources.  

Qualifications:  Quality oriented. Programming and database skills (SQL, XML, and some method of connecting to APIs (e.g. Python, C#, etc). Detail oriented data cleaning experience.  Financial Industry background / interest in the stock market helpful.

In proposal, please provide how many hours you think this project will require. 

We are a dental franchise focused on General, Orthodontic and Pediatric Dentistry. We are looking to use customer analytics to improve quality of care and expand customer base.  The first project is to help us get started, so we may put the right systems and processes in place to become data-driven. In addition, we would like a data expert to undertake the segmentation of our customer base, which is stored in a CRM system, to uncover insights that would lead to better service and expansion of our customer base.  

Business Information

• We have two large full service locations and one smaller satellite location in Las Vegas, NV
• We have been in business for about ten years.
• We now see over 120 patients per day on average.
• We are open seven days a week. We are the largest patient service entity in Las Vegas.
• We have captured roughly 200,000 patients over the last 10 years. About 20% of the Las Vegas Dental Patient Market.

Marketing Information

• We advertise across multiple channels such as web, radio, television and social media.
• We use PRACTICE WEB to schedule appointments
• We use Medicaid to determine patient eligibility
• We send-out advertisements to existing patient addresses and emails.
• We also use SEO

We need a way to meausre the efficacy of our marketing channels to see better understand cost of customer acquisition and customer lifetime value, among other things.

Please let me know what you can do for us in this first phase of the project.  You may also present a roadmap for future phases.  Our team does not possess technologists so you would need to work with us to extract the right information.  If you send us your questions, we are glad to furnish sample data so you may determine what kind of analysis and roadmapping is possilbe at this stage.

I need to hire a data scientist to design a test that can be given to applicants for a full time data scientist position at UpCounsel. I would like a test that involves some type of modeling/algorithm approach while testing their SQL, python, and business accumen knowledge. I would like for someone to understand our business and recommend a problem as well as teh schema for a sample data set. The deliverables would be a test and sample solution. The ongoing work would help me evaluate a candidate's response.

We use postgres, looker, redshift, python, etc.

This project is a continuination of a previous project and will be awarded to the same expert from the previous project.

Financial Portfolio

The scope of the project is to create an application that would support the process of creating offers for the prospective customers. The application need to provide an easy solution to create an inventory of the current portfolio of the customer and provide a mechanism that through calculations propose a portfolio that would be ideal for the prospective customer’s need. The content of the proposed portfolio is filled by the user, but the solution need to provide control mechanisms to facilitate the creation of the new proposed portfolio.

Description

The application will be developed in Excel, it need to work with Excel 2010, 2013 and preferably with 2016 as well.

The application will have the following functionality:

• Data entry for the current and the proposed portfolio
• Possibility to categorize the portfolio items (debt, equity, style box, other categories)
• Overview of the current portfolio from the style boxes perspective Possibility to model the style boxes of the proposed portfolio
• Control mechanisms to show the user if the amounts in the current and/or future portfolio is not allocated correctly (missing amounts, non-balanced amounts)
• Presentation of the current and proposed portfolio in detail in style boxes
• Print layout for the current and proposed portfolio
• Side by side comparison of the present and the proposed portfolio
• Connection to the portfolio categorization data from the existing FPM application
• Possibility to export (copy/paste) portfolio categorization from the FPF to the FPM application

References

• Mockup of the application made in excel during the initial definition of the scope (see attached)
• Notes from the meetings during the definition of the scope – Comments on the mockup (see attached) Present financial portfolio sample (see attached) Proposed financial portfolio sample (see attached)
• Side by side comparison of the present and proposed portfolio (see attached)

InfoScout is the leading provider of real­time shopper insights. Search any brand or retailer to get purchase trends and detailed demographic statistics. ?We collect receipts from a large panel of consumers and have created a massive purchase panel that tracks consumer and household spending longitudinally across many different types of retail outlets and product categories.

Problem we are trying to solve: ?

Using shopper behavior data, household demographics and retailer availability, develop a prediction model that can determine where households are more likely to shop and identify factors that influence their choice of retailer. Identify variables for model development, including those from external data sources ? Perform all data cleaning and manipulation of data set for modeling phases ?

Expertise Required:

Statistics Ph.D. or related ? ML and classification methods (Multi­Class SVM, MNLogit, Bayesian Belief Networks) ? Multiple imputation, sampling methods, factor analysis, PCA,? Distributed processing ?

Our Data Sources:

InfoScout receipt data stored in mySQL database? (~21 Million rows x ~300 columns = ~6.3BN elements) External data source (Experian) format TBD? (Nrows(TBD) x ~3,000 columns)

Our current technology stack:

Vertica v7.1.2­0, MySQL Database, Python, R, Tableau, Microstrategy

Deliverable:

Prediction model that generally explains consumer behavior across a number of inputs (transactions, geo­demographics, other attitudinal data), iteration and refinement, ? Model simulator, ? Summary report of findings,  Model Specs and Diagnostics

Customer Analytics

• A leader in specialty coffee and coffee makers, Keurig Green Mountain, Inc. (KGM) is recognized for its award-winning coffees, innovative Keurig® brewing technology, and environmentally and socially responsible business practices.  The company’s Keurig® Single Cup Brewing System, embodied by a premium brewer portfolio and an expanding family of quality beverage brands, provides consumers the benefits of convenience, variety, and consistent great taste.  Our business model is driven by increasing the installed base of appliances, increasing the daily pods per appliance, and the profit earned per pod.
• Keurig's innovation team is developing a proof of concept presentation showcasing the potential application of detailed customer data for Keurig's marketing, product development, quality, and other organizations.  The assignment is to take the varied sources of data, merge them together, uncover relevant insights & business opportunities, and present the findings in a beautiful powerpoint presentation.  This presentation will be viewed by high-level executives -- it must be aesthetically pleasing, thought-provoking, and easily digested.
• The assignment requires a data analytics expert who can: merge and manipulate the data, understand the relevant business objectives in order to uncover insights, be creative in identifying insights, and skillfully present the findings in powerpoint format.
• Keurig-provided data sources will come in the form of excel files.  No analytical or visualization software will be provided to the vendor -- vendor must use his/her own.
• Data provided will include consumer brewing behavior, household demographics, and (limited) pod sales data
• The final deliverable will be two presentations:  one based on opportunities for Keurig and one based on opportunities for Keurig's partners.
• In the project briefing (and on-demand throughout the project), Keurig will provide contextual background on the business objectives and business models.
• The project must be completed by November 25, 2015.
• Payment terms are Net 40 after receipt of final deliverable (ignore payment schedule in project overview).

We are a consumer health startup that helps people build personalized healthy lifestyles. We need a data expert to help us describe the artificial intelligence and analytics plan for a provisional patent application of our information technology system.

We are looking for a data expert with the following experiences.

1. Broad range of artificial intelligence including:

• Prioritization algorithms
• Recommendation algorithms
• Adaptive learning algorithms
• Machine learning algorithms

2. User Profile Analytics

• Performance metrics
• Scoring metrics

3. Describing AI models, algorithms, and analytics for provisional and utility patent applications

System Description

The function of the system is to enable users with a given health goal (e.g. weight loss, asthma, etc.) to discover consumer health solutions (products, services and behaviors) that might be effective for them. Instead of adhering to a generic program say for weight loss, users will be provided with tools to intelligently personalize a repertoire of solutions.

As part of this process, data collected about the user by various means will be used by an AI system to prioritize and recommend assessments, challenges, and solutions.

The process supported by the system, and the algorithms and analytics that enable this process are the core of the provisional patent application.

Similar Systems

Netflix, Pandora, and Khan Academy are example systems that illustrate the type of algorithms we are looking to apply. Though they share some similarities to the present system in other domains, they are substantially different in process and function.

In each of these systems, user data is gathered to create a profile, which in turn is the basis for prioritized recommendations from a database of movies, music, or educational modules. Based on user choices and outcomes, adaptive learning algorithms are applied by at least one of these systems. In iterative fashion, the best experiment, or recommendation, is identified for a given user to yield the most information for determining the best experiment in the next iteration.

Deliverable

AI and analytics plan for a provisional patent application

Requirements

1. Provisional patent applications require:

• Enough detail to clearly describe the claimed invention
• Claim a broader range of AI approaches than will ultimately be implemented or applied for in the follow utility patent application. Claiming this broader range in the provisional patent application is important, as it sets the date for the scope of our claim in the follow up utility patent application.

2. Prioritization engine and Recommendation engine description The application requires describing Data in/Transformation of data/Data out. We already have a list of data elements that can be used as input.

• We need help with determining the range of AI models, and how they would be applied to the data elements to prioritize and recommend assessments, challenges, and solutions. We think adaptive learning algorithms are a strong candidate, but as mentioned, we are looking for a range of AI models.
• The algorithms do not need to be made in real time, but rather on a nightly/daily basis.

3. User Profile Analytics As users repeat the process of discovering solutions, they will collect those solutions in their profile. User metrics need to be calculated to improve the next round of prioritizations and recommendations. We have a rough draft of Performance metrics and Scoring focused on determining effectiveness and sustainability of the set of solutions collected and how well they fit other user profile data.

• We need help refining and describing these Performances Metrics and Scoring and how they would be used by the prioritization and recommendation engines for the application.

4. Integration of analytics plan into existing draft of provisional patient application Our patent writer has already begun a draft of the application, and our system architect has created the system architecture. We have all the pieces required for the application except for the AI/analytics plan.

• The AI/analytics plan needs to be integrated into the application. You will be able to work with both the patent writer and the system architect.

5. Sign a Non-Disclosure Agreement

Work done so far:

• Detailed system description of process, user flow and features
• System architecture
• Data elements defined, though no data has yet been collected
• Basic examples of graphical user interface

Reference patents identified The AI/analytics plan is the remaining piece of the provisional patent application.