Data Scientist

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.