Senior Data Scientist, Tonal

• Bachelor’s degree in Statistics, Mathematics, Computer Science, Data Science, Economics, or a related field (Master’s preferred) with at least 5+ years of experience in data analysis
• Proven expertise in SQL, Python, Pandas, and advanced knowledge of statistical methods, data modeling, and machine learning software, like SKLearn and TensorFlow
• Strong experience with data reporting and analysis tools, like Looker, Databricks, Snowflake
• Proven expertise in delivering innovative and effective solutions to complex challenges, with a deep understanding of the interplay between various disciplines, and the capacity to lead the development of new policies and strategic initiatives
• Demonstrated ability to analyze intricate data and scenarios, identify suitable methodologies and processes, and apply sound judgment in adapting techniques to achieve optimal outcomes
• Demonstrated ability to effectively communicate data-driven insights to both technical and non-technical stakeholders

Desirable

• As a Senior Data Scientist - Analytics, you will play a pivotal role in driving data-informed decisions across our organization.
• This role requires a deep understanding of data analytics and modeling, experience and aptitude to manage internal stakeholders, and ability to maintain aspects of our data warehouse to support product development and business strategy.
• You will work with tools like Databricks, DBT, Python, and Looker, utilizing your expertise to generate insightful reports that influence business decisions all while serving as the primary relationship owner of the stakeholders you manage.
• As a data scientist, you will be partnering with the software, sports science, product, and strategy teams on a wide array of focus areas and needs
• Design, develop, and maintain complex data models, queries, and automated ETL pipelines using tools like Python, Databricks, Snowflake, Pandas, and DBT to extract actionable insights from large datasets
• Prepare and present comprehensive reports, dashboards, and visualizations, ensuring data is accessible and understandable to stakeholders across the organization
• Collaborate with cross-functional teams, including product managers and engineers, to define data requirements, identify trends, and drive business decision-making aligned with organizational goals
• Apply statistical methods and machine learning techniques, to analyze data, evaluate KPIs, and provide strategic recommendations for business improvements
• Mentor junior data analysts, promote best practices, and stay current with industry trends and advancements in data analytics to continuously improve processes and tools