Data Scientist

Data Scientist (Marketing Science) Seattle, WA 12 months $55/hr - $60/hr Overview: We are seeking a Data Scientist with a strong background in marketing measurement, causal inference, and experimentation. This individual should have a passion for building data-driven products, the ability to develop insights and scientific vision, and a proven track record of executing complex projects that drive business impact. Day to Day: • Develop and enhance Marketing Mix Models (MMM) to measure channel effectiveness, optimize budget allocation, and quantify ROI • Build and refine Customer Lifetime Value (CLV) models to support acquisition, retention, and segmentation strategies • Design and analyze A/B tests and quasi-experiments (geo holdouts, diff-in-diff, synthetic controls) to measure campaign lift • Partner with marketing teams to turn insights into actionable recommendations (targeting, creative, channel mix) • Collaborate with data scientists, ML engineers, and business stakeholders to productionize measurement solutions Required Knowledge & Skills: • Experiment design • PhD, or Master's + 4+ years in CS, CE, ML, Statistics, Economics, or related field • 3+ years building machine learning models or algorithms for business applications • Experience with causal inference methods (A/B testing, diff-in-diff, instrumental variables, propensity scoring, synthetic controls) • Familiarity with cloud tools (AWS: S3, SageMaker, EMR, EC2) • Programming experience in Python, R, or similar • Machine Learning — hands-on experience building predictive models (regression, gradient boosting, survival models, or deep learning for sequential data). Should be comfortable with model training, validation, feature engineering, and productionization. • Causal Inference — understands experimental design (A/B tests, holdouts), uplift modeling, or econometric techniques (diff-in-diff, instrumental variables). We need someone who can distinguish correlation from causation and design measurement that's defensible. • Python fluency — primary working language. Comfortable with pandas, scikit-learn, PyTorch/TensorFlow, and standard DS tooling. • Cloud computation — experience with AWS (SageMaker, EMR, Redshift/Athena) or equivalent. Must be able to work with large-scale data pipelines, not just local notebooks. Nice to Have: • Experience in marketing science or marketing analytics • Knowledge of emerging marketing tech and measurement trends • Exposure to large-scale data science applications (tech or retail) • Background in ML, NLP, computer vision, or related domains • Marketing science experience — prior work on LTV, attribution, incrementality, customer segmentation, or marketing mix modeling. Understands how models translate into marketing decisions (targeting, budget allocation, campaign optimization). • Experience working with cross-functional partners (marketing, engineering, finance). Exact compensation may vary based on several factors, including skills, experience, and education. Benefit packages for this role will start on the 31st day of employment and include medical, dental, and vision insurance, as well as HSA, FSA, and DCFSA account options, and 401k retirement account access with employer matching. Employees in this role are also entitled to paid sick leave and/or other paid time off as provided by applicable law.