Data Scientist

We are seeking a Sr Data Scientist to join our team supporting Consumer Packaged Goods marketing and media analytics. The ideal candidate will have strong experience in statistics, machine learning, experimentation, and causal inference and a proven ability to ship decision-ready models and translate insights into measurable business outcomes., * Partner with data science leadership, ML engineers, and CPG marketing stakeholders to build and deploy predictive and optimization models on modern cloud platforms.

• Lead technical workstreams, frame ambiguous problems, define evaluation criteria, and set a roadmap from prototype to production.
• Develop measurement and incrementality strategies using experimentation and causal inference such as A/B tests, geo tests, Difference-in-Differences, Regression Discontinuity, and causal ML.
• Build marketing response and demand models including uplift and propensity, time-series forecasting, and hierarchical models for planning, targeting, and budget allocation.
• Design and implement scalable feature engineering and model monitoring for robustness, reproducibility, and sustained performance.
• Translate complex outputs into actionable narratives for marketing, finance, and leadership, communicating uncertainty, tradeoffs, and recommended actions.
• Establish best practices for experiment design including power analysis, guardrails, and interpretation of results.
• Advise partners on data strategy including instrumentation, taxonomy, data quality, and metrics for CPG brand and performance outcomes.
• Contribute to team strategy, documentation, and technical standards; mentor junior data scientists through reviews and coaching.
• Collaborate to operationalize models via APIs, batch scoring, and dashboards to ensure adoption and impact.

Do you have experience in Version control?, Do you have a Bachelor's degree?, * 6+ years of hands-on data science experience delivering end-to-end statistical and machine learning solutions.

• Strong proficiency in Python and SQL; experience with scikit-learn, XGBoost or LightGBM, PyMC or Stan, and MLflow; solid software practices including version control, testing, and reproducibility.
• Bachelor's degree in a quantitative field such as Statistics, Mathematics, Economics, Computer Science, or Data Science.
• Demonstrated expertise in causal inference and experimentation including DAGs, identification, regression-based methods, and quasi-experiments, with clear communication of limitations and assumptions.
• Experience with marketing and growth models such as forecasting, response or uplift, segmentation, and optimization; MMM familiarity is a plus.
• Experience with large, messy datasets and strong data wrangling and feature engineering skills.
• Proven ability to influence decisions through clear storytelling and stakeholder management with measurable impact.
• Self-starter with effective prioritization, problem-solving, and time management in a fast-moving environment.
• Experience with cloud data and AI platforms such as Azure, GCP, or AWS and production analytics patterns.

Preferred Skills:

• Graduate degree in a quantitative discipline (MS or PhD).
• Experience in CPG or adjacent retail and consumer industries, including syndicated data such as POS and panel, trade and promo dynamics, and omnichannel measurement.
• Background in marketing analytics, experimentation, or consulting or agency environments with delivery to executive audiences.
• Experience partnering with engineering to deploy models and build data products including batch or real-time scoring, APIs, and dashboards.

3.33.3 out of 5 stars Remote $60 - $80 an hour - Contract