Staff Data Scientist

What you'll do...

Position: Staff Data Scientist

Job Location: 850 Cherry Avenue, San Bruno, CA 94066

Duties: Develop and enhance ads measurement methodology across sales lift, synthetic control group, ghost ads, MMM, MTA, A/B testing, Geo-experimentation, and randomized Control Tests. Process complicated and large-scale datasets using distributed computing platforms, extract insights from data, predict future trends, and optimize business metrics. Develop measurement methodology, manage ambiguous problems, generate hypotheses, and provide recommendations to Engineering, Product, and Data science teams. Use statistical methods to evaluate the performance of machine learning and statistical models in marketing measurement products. Define vision and strategies for Walmart ads measurement methodologies including Sales Lift, Search Incrementality, WAMM, and MTA. Identify market opportunities and build business cases. Drive product development through ideation, methodology development, prototyping, gathering product requirements, defining scalable product roadmaps, determining rollout strategy, managing risks, and facilitating the transition from initial concepts to enterprise ready. Conduct research of existing and new ads measurement methodologies through reviewing academic papers, white papers, and industry research. Use Conversion Lift, Brand Lift, Private Lift, Open source MMM packages, Advanced Analytics, Adobe Experience Cloud, Advanced Measurement API, and Conversion API to scale Walmart Ads Measurement Products. Reconcile results from a variety of Ads Measurement solutions and other industry offerings, open-source solutions, and client specific solutions to provide actionable insights with the objective of improving campaign performance. Collaborate with cross functional teams including engineering, data science, product, sales, and UX teams across different phases of product development.

Minimum education and experience required: Master’s degree or equivalent in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 2 years of experience in an analytics related field; OR Bachelor’s degree or equivalent in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 4 years of experience in an analytics related field.

Skills required: Experience coding in SQL, R, and Python to create statistical models. Experience building econometrics models for statistical analysis to measure the effectiveness of ad campaigns. Experience building machine learning models to evaluate campaign effectiveness and calculate return on investment. Experience with data science and causal inference techniques in marketing including Conversion Lift, Brand Lift, and Clean Room studies to help advertisers improve their Return on Ad Spend and other campaign performance metrics. Experience with Business Intelligence tools including Tableau, PowerBI, Google Analytics, and Looker. Experience with Marketing Technology, Web Analytics, Campaign Analytics (Adobe Analytics, Google Analytics, and Facebook Business manager) for tracking ad campaign performance and analyzing e-commerce performance. Experience with Marketing Revenue attribution methods (Mixed Media Model and Multi-Touch Attribution) for evaluating Ad campaign performance and providing recommendations on optimizations. Experience with Testing methodology (A/B testing, Ghosts Ads, Intent to treat, Synthetic Control, and Geo-Experiments) to run market experiments and recommend marketing strategy to advertisers. Experience with Time series modeling (Linear regression, Logistics regression, and random forest) to create revenue forecasts. Experience with Agile methodology and JIRA for project management and software development. Experience with Meta/Facebook Ads Measurement tools including Conversion Lift, Brand lift, Private Lift, Advance Analytics, Advanced Measurements API, Conversion API, ROBYN (MMM), GEO-Lift, and Prophet Models. Experience with Azure Cloud Platform, Databricks, Azure Data Factory, Snowflake, Presto, and Google Cloud Platform to analyze large datasets and run ML models in cloud environments. Employer will accept any amount of experience with the required skills.

Salary Range: $168,110/year to $