Operations | Austin, TX | Full Time
Revionics, the leading provider of SaaS-based pricing, promotion, markdown and space solutions, is seeking a Data Scientist. This individual will work as part of the Science Development Team to research and develop analytical, optimization, and forecasting solutions for use in our end product to retailers. The successful candidate brings a balance of creative problem solving, statistical skills, hands-on data skills, and practical analytic skills to the organization. Strong communication and presentation skills are also highly desired.
Who you are:
- Develop a deep understanding of the core science behind Revionics’ solutions.
- Create analytic applications to deliver insights for customers that will help them more efficiently and successfully use Revionics’ solution.
- Automate and improve the reusability and efficiency of existing analytics using a combination of scripting languages, SQL, NoSQL, and in-house software tools.
- Use strong mathematical and analytic skills along with an ability to understand and use statistical solutions to solve business problems
- Communicate technical information to both internal and external clients
What you Have/Can Do as a Minimum:
- Bachelor’s degree in Computer Science, Engineering, Mathematics, or equivalent
- Strong Python skills
- Proficiency with Data Science tools (Scikit-learn, Pandas, etc.)
- Proficiency in Data Science methodologies/practices (e.g. model validation, model selection, forecast accuracy analysis, etc.).
- SQL and relational databases skills (MS SQL Server, Oracle, etc.)
- Data visualization skills and ability to present complex information to technical and non-technical audiences.
What you can Do to Stand Out:
- Graduate degree in Computer Science, Engineering, Mathematics, or equivalent
- Strong Proficiency with Data visualization libraries (Bokeh, Matplotlib, d3.js)
- Familiarity with statistical regression and modeling techniques (least squares, maximum likelihood, Bayesian estimation.)
- Familiarity with Classification and Clustering methods (K-means, Non-hierarchical, etc.)
- Compiled software development languages (C++, C#, Java)
- Familiarity with Retail or a similar industry (supply chain, financial, credit, etc.)
- Familiarity with Econometrics, Financial Optimization, or Optimization domain knowledge
- Numerical Methods and Scientific Computing
- Applied Numerical Linear Algebra
Who We Are:
Predictive. Prescriptive. Profitable Retailing.
Retailers in all segments across the world adopt our self-funding model to improve top-line sales, demand, and margin. Our customers gain a competitive edge and improve their value proposition while outmaneuvering competitor price aggressiveness.
Our 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