Data Scientist Specialist (Marketing)

What You’ll Do
You’ll design and deliver data science solutions that blend cutting-edge methods with practical deployment. Working across industries and use cases, you’ll tackle challenging problems in marketing analytics, build robust models, and deliver insights that power client-facing tools and internal decision-making.

• Develop End-to-End Models: Design, train, and evaluate models for marketing mix modeling, incrementality measurement, and ads optimization to inform media planning and budget allocation.
• Collaborate on Real-World Solutions: Partner with software engineers and fellow data scientists to integrate data-driven models into deployable systems that operate in dynamic production environments.
• Client-Focused Problem Solving: Work closely with stakeholders to frame ambiguous marketing problems, explore solution paths, and translate technical insights into actionable recommendations.
• Explore, Iterate, Validate: Lead the exploration and analysis of large-scale datasets using tools like Pandas, NumPy, and Spark to inform model design, evaluate performance, and identify optimization opportunities.
• Research-Driven Innovation: Stay current with advances in econometrics, causal inference, and machine learning techniques relevant to ads measurement and optimization, adapting them for practical application.

What We Need

Professional Experience:

• 2+ years of hands-on experience building and deploying models in marketing analytics, ads optimization, or related domains.
• Proven ability to take models from prototype to production in Python-based workflows.
• Experience working in client-facing roles or directly engaging with stakeholders to refine project requirements.

Technical Expertise:

• Strong proficiency in Python and commonly used ML/data libraries (Pandas, NumPy, scikit-learn, PyTorch, or similar).
• Familiarity with marketing mix modeling (MMM), attribution modeling, or causal inference techniques.
• Experience working with large-scale datasets using distributed tools such as Spark.
• Comfort navigating cloud environments (GCP, AWS, or similar); Databricks experience is a plus.
• Solid grasp of experimental design, model evaluation, and data debugging practices.
• Strong code hygiene: able to write clean, modular, testable code in collaborative environments.

We offer a pay range of $30+ per hour, with the exact rate determined after evaluating your experience, expertise, and geographic location. Final offer amounts may vary from the pay range listed above. As a contractor you’ll supply a secure computer and high‑speed internet; company‑sponsored benefits such as health insurance and PTO do not apply.

Important:

All candidates must pass an interview as part of the contracting process.