Data Scientist, Algorithms, Optimization - Fulfillment

Responsibilities

• Leverage data and analytic frameworks to direct creations and improvements of algorithms and models underpinning the team’s systems and products
• Partner with Engineers, Product Managers, and Business Partners to frame problems, both mathematically and within the business context
• Perform exploratory data analysis to gain a deeper understanding of the problem
• Construct and fit statistical, machine learning, or optimization models
• Write production modeling code; collaborate with Software Engineers to implement algorithms in production
• Design and implement both simulated and live traffic experiments
• Analyze experimental and observational data; communicate findings; facilitate launch decisions
• Develop measurement methodologies to monitor the health of our products, as well as the impacts on user outcomes and marketplace outcomes
• Drive collaboration and coordination with cross-functional teams

Requirements

• M.S. or Ph.D. in Machine Learning, Statistics, Operations Research, Computer Science, Mathematics, or other quantitative fields
• 2+ years professional experience in a technology company setting
• Proven experience with building and evaluating machine learning models
• Proficiency with Python and working in a production coding environment
• Passion for solving unstructured and non-standard mathematical problems
• End-to-end experience with data, including querying, aggregation, analysis, and visualization
• Strong oral and written communication skills, and ability to collaborate and communicate with others to solve a problem

Qualifications

• Experience developing and deploying machine learning models in production environments
• Experience with data manipulation and analysis tools such as SQL, Pandas, NumPy, Matplotlib, Seaborn, etc.
• Experience with machine learning libraries such as Scikit-Learn, TensorFlow, PyTorch, etc.
• Experience with statistical methods and techniques for model evaluation and selection
• Experience with data visualization tools such as Matplotlib, Seaborn, Plotly, etc.

Skills

• Python programming
• Data analysis and manipulation
• Machine learning and statistical modeling
• Collaboration and communication

Benefits

• Great medical, dental, and vision insurance options
• Mental health benefits
• Family building benefits
• Child care and pet benefits
• 401(k) plan
• Discretionary paid time off
• 18 weeks of paid parental leave
• Subsidized commuter benefits
• Lifty Pink - exclusive benefits for team members
• Flexible work schedule with option to work remotely up to 4 weeks per year

Pay

Your recruiter can share more information about the salary range specific to your working location and other factors during the hiring process. Range is not inclusive of potential equity offering, bonus or benefits.

Schedule

This role will be in-office on a hybrid schedule — Team Members will be expected to work in the office 3 days per week on Mondays, Wednesdays, and Thursdays. Hybrid roles have the flexibility to work from anywhere for up to 4 weeks per year.