Data Science Analyst
Role and Responsibilities:
Revionics has an immediate opening in our UK office in the 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 and experience in a related analytics role are desired. This position may require up to 20-30% travel, mostly to sites across the EU.
What you’ll do:
- Develop a solid understanding of Revionics’ core set of science services and of the science behind Revionics’ solutions,
- Execute and deliver analytical services for customers. Examples include Data Validation, Pricing Strategy Analysis, Key Value Item identification, Basket Analysis, Store Clustering and Promotion Performance Analysis,
- Assist in analyzing results from Revionics’ demand models 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,
- Work with Price Strategy Consultants, Project Managers, Systems Engineers, and Client Partners in the delivery of data science services and sharing of analytical insight as part of client projects,
- Collaborate with other members of the science teams to help improve automation & efficiency of existing science services and analytic workflow scripts using a combination of Python, SQL, Google Cloud Platform tools and in-house software tools
What you have:
- 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 problem-solving skills and ability to interpret analytic results and diagnose issues using structured, data-driven methods
- 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 etc),
- Data visualization skills (Tableau highly desired) and ability to present complex information to technical and non-technical audiences,
- Strong communication and presentation skills
How you can stand out:
- Proficiency with Python, JuPyter notebooks, SciPy, numPy
- Familiarity applying analytics in industry (Retail, financial, credit, etc.)
- Strong proficiency with visualization tools and 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.)
- Fluency in German, Russian, Spanish or other European languages
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