Data Science - Optimization

Qualifications
Bachelor's degree, Master's preferred, in mathematics, data science, computer science, operations research, engineering, or related area required.
3+ years of experience, with demonstrable skills writing software in SQL, Python, Java, or C-languages, and utilizing Linear Programming, MIP, Convex Optimization, Differential Calculus.
2-5 years of relevant work experience.
Experience with ETL, cleaning and integrating data in data warehouse.
Experience with large data analysis models, using relational and non-relational databases.
Experience with collaborative software development best practices, including version tracking and code reviews using GitHub.
Understanding of enterprise-scale business and its processes.
Strong critical thinking skills and attention to detail.
Good English language skills.
Preferred
Experience solving deep operations / supply chain problems and instituting rigorous performance monitoring process.
Experience with tradeoffs between speed, performance, and scalability in optimization.
Experience with Spark, data warehouse, data lake or lakehouse.
Experience using advanced statistical and machine learning techniques to analyze large datasets.
Experience leading and mentoring analysts and technical team members.
What You Offer
Entrepreneurial: You're personally invested in fulfilling our mission and growing the business. You're constantly thinking outside-the-box and proposing new ideas that may influence our broader strategy and product roadmap.
Commando Mindset: You aren't afraid to parachute into a metaphorical jungle, build data systems from scratch, and define solutions to complex problems. You're an independent self-starter that is adaptable to change.
Team-Oriented: You recognize the whole is greater than the sum-of-its-parts and work well with others. You are coachable and willing to invest in others.
Data-Driven: You believe in hypothesis testing, iterative experimentation, and incremental delivery. You value underpinning conclusions with empirical evidence over unsubstantiated claims.