Position: - Senior Data Scientist
Location: - San Francisco, New York, Seattle, or Little Rock - Need to work PST time
Duration: 12 months +
Rate: DOE
You will:
- Lead measurement initiatives; develop KPIs and learning plans for customers in support of their marketing objectives.
- Develop, implement, and maintain analytics systems, tools, and frameworks that enable ecient analysis for customers.
- Design approaches for observational analytics, including mining multi-dimensional datasets, and experimental methods to build templates and libraries of analysis that can scale across various customer use cases and verticals.
- Consult and advise clients and internal teams on audience strategy, experimental design, data requirements gathering, and post-campaign measurement using statistical and mathematical concepts to drive business solutions and actionable recommendations.
- Get hands-on with customer data to drive insights, answer key business questions, and enable campaign optimization.
- Identify and communicate areas to improve effectiveness, eciency, and productivity.
- Create compelling presentations and effectively communicate complex analytical concepts to business and technical audiences.
- Speak and present both internally and externally, leveraging data to tell a story.
- Build up a strong understanding and expert knowledge of the various data sources brought together for data enrichment and collaboration.
- Work directly with customer stakeholders to gather requirements, communicate updates and ndings, and build relationships.
Your team will:
- Work closely with product and engineering teams to support and understand the cloud infrastructure that runs the models.
- Dive deep with internal and external clients to understand their measurement and analytical needs and translate them into product improvements.
- Help design new offerings in the analytical space.
About you:
- Bachelors with 10-15+ years of experience, Masters with 3+ years of experience, or PhD with 0-2 years of experience in a data science related eld (mathematics, statistics, computer science, etc.).
- Strong command of probability and statistics.
- Fluency in data and statistical analysis using SQL, Python, and PySpark.
- Strong command of data science toolkits (Pandas, NumPy, scikit-learn, etc.)
- Understanding of cloud platforms (AWS, Google Cloud Platform, etc.) and relational databases.
- Familiarity with fundamentals of randomized-controlled trials, A/B testing, and mar-tech/ad-tech measurement.
- Strong understanding of large-scale data analysis, ne-tuning of Spark jobs, and optimizing Spark SQL/PySpark models.
- Knowledge of Business Intelligence tools to build visualizations.
- High EQ.