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Internal Application: Data Science Analyst

Implementation | Austin, TX | Full Time

Job Description

Role and Responsibilities:

Role and Responsibilities:

Revionics has an immediate opening on our Science Services team for a Data Science Analyst. This individual will work in a fast-paced environment as part of multi-disciplinary project teams to deliver analytic services to retailers.  The successful candidate will bring a balance of creative problem solving, hands-on data skills and practical analytic skills to the organization. Strong communication skills highly desired.

The Data Science Analyst’s responsibility is to support the Science Services team to:

  • develop a solid understanding of Revionics’ core set of science services and of the science behind Revionics’ solutions,
  • execute and deliver Revionics analytical services for customers to deadline. Examples include Data Validation, Key-Value Item identification, Market Basket Analysis, Store Zone Clustering, etc.,
  • Assist in analyzing results from Revionics’ demand modeling and forecasts using hindcast holdout sample and modeling tuning techniques,
  • Assist in Value Measurement analysis to demonstrate the value of our price optimization solution for existing customers,
  • assist with improve automation & efficiency of existing science services using a combination of Python, SQL and in-house software tools,
  • work with Price Strategy Consultants, Project Managers, Systems Engineers, and Client Partners in the delivery of science solutions,
  • work closely with other members of the Science teams for collaboration, support and to help integrate software tools such analytic workflow scripts, data validation & testing scripts, data visualization tools, etc.


  • Masters (preferred) in Operations Research, Econometrics, Data Science, Mathematics, Physical Sciences or equivalent,
  • Strong quantitative, mathematical and analytic skills and ability to understand use of statistical solutions to business problems
  • Strong data skills including experience with outlier identification and data cleansing
  • SQL and relational databases skills (MS SQL Server, Oracle, etc.) 
  • Experience with analytic scripting languages applications (Python highly desired, R, MatLab, Alteryx.) 
  • Data visualization skills (Excel, Tableau (highly desired)) and ability to present complex information to technical and non-technical audiences.
  • Strong communication and presentation skills

Preferred Candidate Attributes:

  • Proficiency with Python, JuPyter notebooks, SciPy, numPy
  • Familiarity applying analytics in industry (Retail, financial, credit, etc.)
  • Proficiency with Visualization Business Intelligence applications (Tableau, Alteryx, etc.)
  • Familiarity with statistical regression and modeling techniques (least squares, maximum likelihood, Bayesian estimation.)
  • Familiarity with Classification and Clustering methods (K-means, Non-hierarchical, etc.)
  • Software development languages tools (C++, C#, Java)
  • Familiarity with data load and ETL / Automation tools (Informatica, etc.)


Who We Are:

Predictive. Prescriptive. Profitable Retailing.

We provide SaaS-based pricing, promotion, markdown and space solutions. Retailers in all segments across the world adopt our self-funding model to improve top-line sales, demand, and margin. Our customers gain that competitive edge and improve their value proposition while outmaneuvering competitor price aggressiveness.

During the days of first-generation price optimization solutions, at a time where science in retail was viewed as voodoo, our founder Jeff Smith nurtured the concept that there could be a better way. He went on to form Revionics around that new-generation vision, and to this day we remain committed to his goal:  To help retail businesses and everyday users solve complex pricing challenges leveraging the latest machine learning science with a completely transparent process, usable in an intuitive way that fits into retailers’ normal business flows.

Our company success is based on our 4 foundational pillars: 

  • A SaaS-based architecture for fast ROI
  • Productized, transparent science
  • Machine Learning algorithms that continue to evolve with changing market conditions and shopper behaviors for built-in future proofing
  • A supportive culture focusing on both our people and customers’ well-being.

Our Core Values:

  • Integrity: Be honest, dependable and complete
  • Transparency: Anticipate questions and give clear, usable answers.
  • Continuous Improvement:  Be relentless about improvement – for ourselves and our customers
  • Curiosity: Shine lights in dark corners; seek to ensure we know what we don’t know
  • Accountability: Own the problem and the solution
  • Dedication: Don’t stop until the numbers are right and systems are up
  • Humility: Put the spotlight on our customers, not ourselves