Machine Learning Engineer US Remote

We are the recognized leader in AI-powered pricing and promotions. Global brands and retailers rely on the platform to optimize pricing in response to market conditions and to deliver higher ROI on promotional spend. Our Retail Pricing Suite and Offer Innovation Suite solutions are driving strong margin and sales volume improvements for leading companies such as Coca-Cola, Frito-Lay, Raley’s, and Walgreens. Founded in 2013, we are headquartered in Palo Alto, California.

Reporting directly to the CTO, you will be at the center of what determines our success as a company. You will analyze the data and develop production code using the newest Data Science and Machine Learning techniques to determine the optimal prices and promotions for major product manufacturers and retailers that sell these products.

Who You Are You are an analytical, framework thinker

You are comfortable in a fast-paced environment

You are highly collaborative

You are very strong technically, with a good ability to translate a business problem into a technical one

You are business focused; measures work in its contributions to business outcomes and prioritizes effort against deliverables accordingly Your Qualifications You have 2+ years of experience in Data Science or Machine Learning

You have an BS., M.S., or PhD in Computer Science, Machine Learning, Statistics, Mathematics, Engineering, Economics, Operations Research, or relevant quantitative field

You have excellent coding ability. Able to write optimized Python code (vectorization, lazy evaluation, etc.)

You are experienced with NumPy and Pandas

You have experience in test-driven development strongly preferred

You are strong in math (Linear Algebra, Calculus, etc.) and numerical problem solving (e.g. optimization)

You are experienced with Generalized Linear Models

Experienced in A/B testing and Design of Experiments preferred

Agile experience preferred

Familiarity with standard econometric methods is a big plus

Demand Modeling, Forecasting, Pricing, and Causal Inference experience a plus

Strong in statistics relevant to Machine Learning preferred (hypothesis testing, Bayesian methods, regressions, maximum likelihood estimation, etc.)

Nice to have: Neural Networks (Deep Learning, Embeddings, Sequence Modeling, CNN), Tree-based methods (GBDT, Random Forest), Regularization Methods (L1/L2 penalties, Feature Selection, Dimensionality Reduction) What You’ll Do You will generate ideas and quickly turn them into efficient, well-tested, functioning code in our Python codebase

You will partner with the Engineering team to create highly scalable solutions

You will research, implement and modify modern Data Science techniques. More specifically: Build Statistical and Machine Learning models that describe the impact of prices and promotions on shopper behavior, including behavioral pricing effects. You’ll need to find middle ground between using flexible modern AI methods and proven classical methods. Develop Optimization and Experiment Design systems, which determine the best prices to set for each product in each store each week. Finding a good balance on the exploration-exploitation tradeoff will be important Design and run pricing experiments across hundreds of stores and tens of thousands of products Create model validation methods to make sure that our models are accurate and to quantify the impact of our solutions on the clients’ bottom line

You will collaborate with the team to prioritize new feature development by assessing potential impact What’s in it for You You will experience the excitement of working at and growing with an expanding venture-backed SaaS startup where you can make a huge difference

You will be part of an exceptionally talented team that retains a significant focus on personal and professional development

You will be part of a significant period of growth for the business Location

Remote US

Eversight Culture, Benefits, and Perks

At Eversight, we’ve pivoted our benefits offerings to support the current remote work environment in addition to our standard core offerings. We provide: Competitive pay and equity

Medical, dental, vision, and 401k

Unlimited vacation policy

Reimbursement for professional development

Flexible parental leave

Remote office expense reimbursement

Lifestyle Spending Account to support your physical, mental, and emotional wellness

Commitment to community service through multiple service events per year (we’ve taken this virtual for now!)

Employee milestone service award program