Analysis Skills, Bayesian Networks, Budgeting, Campaigns, Cloud Computing, Computer Science, Data Management, Data Science, Data Sets, Data Warehousing, Economics, Experiment Design, Finance, Forecasting, Instrumentation, Machine Learning, Machine Tool, Marketing, Mentoring, Metrics, Python Programming/Scripting Language, Quality Management, Quantitative Analysis, R Programming Language, SQL (Structured Query Language), Snowflake Schema, Statistics
About the Role
We are looking for a Senior Data Scientist to lead measurement and analytics within a fast-moving marketing technology (MarTech) environment. In this role you will be the analytical backbone behind how marketing performance is measured, understood, and improved. You will partner closely with marketing, engineering, product, and finance teams to design measurement frameworks, quantify the impact of campaigns and channels, and turn complex data into clear, decision-ready insights. This is a high-impact, high-ambiguity role suited to someone who enjoys defining the right questions as much as answering them, and who can operate independently across a large and evolving data landscape.
A Typical Day
- You will design and own marketing measurement methodologies, including incrementality testing, marketing mix modeling, multi-touch attribution, and experiment design.
- You will build statistical and machine learning models to evaluate channel effectiveness, forecast outcomes, and inform budget allocation.
- You will translate ambiguous business questions into rigorous analytical plans, then deliver findings to both technical and non-technical stakeholders in a way that drives action.
- You will collaborate with data engineering to improve the quality, structure, and reliability of marketing data pipelines, and you will define the metrics and instrumentation needed to measure what matters.
- You will also mentor other analysts and data scientists, helping raise the analytical bar across the team.
Skills
Your Expertise:
- You bring 5 or more years of experience in data science or quantitative analytics, with a strong track record in marketing measurement, experimentation, or causal inference.
- You are highly proficient in SQL and Python (or R), and you are comfortable working with large, messy, real-world datasets.
- You have hands-on experience with at least one of the following: incrementality and lift testing, marketing mix modeling, attribution modeling, or A/B and experiment design.
- You have a solid foundation in statistics and causal inference, and you can clearly explain the assumptions and limitations behind your methods.
- You are able to work independently in an ambiguous environment, scope your own problems, and communicate results persuasively to senior stakeholders.
Preferred Qualifications
- Experience supporting marketing or growth functions at a large consumer technology company, online marketplace, or platform business is strongly preferred.
- Familiarity with modern MarTech and measurement tooling, cloud data warehouses (such as BigQuery, Snowflake, or Redshift), and workflow tools (such as dbt or Airflow) is a plus.
- Exposure to media measurement in a privacy-conscious environment, Bayesian methods, or production-grade model deployment is also valued.
- An advanced degree in a quantitative field (statistics, economics, computer science, or similar) is welcomed but not required.
Key Details
- Location: Remote
- Start Date: June 2026
- Duration: 6-12 months, with strong possibility of extension
- Work Schedule: Full-time, 40 hours per week (8 hours/day, 5 days/week)
- Pay Rate Range: $75-$110 per hour