Senior Data Scientist I

Job Summary
In this role, you will join a team focused on research surrounding hardware, software, and business rules that support the delivery of high-quality products to our clients. You will learn and become an expert in panel and meter data—managing measurements, analyzing patterns, and evaluating how we can continuously optimize data collection and crediting.
Working independently, you will modify codebase for ongoing products, conduct feasibility research, explore analytical models, and evaluate business cases using data from panels and meters.
Key Responsibilities
Core Analytics & Product Support:
Modify existing code and support ongoing products to optimize performance and efficiency.
Execute feasibility research on new projects and explore innovative models and algorithms.
Evaluate and refine business cases using panel and meter data; manage measurement strategies to identify patterns, analyze trends, and drive continuous improvement.
Data Engineering & Execution:
Independently design analysis plans and build robust, underlying data pipelines using Python, PySpark, and SQL.
Incorporate quality checks throughout the data pipeline to proactively detect and correct errors.
Leverage AI and best practices to seek out and implement quality or efficiency improvements in methodologies and processes.
Project & Stakeholder Management:
Independently manage and lead end-to-end analytics projects, ensuring timelines and key deliverables are met.
Collaborate effectively with cross-functional department stakeholders (Product, Operations, Engineering, Data Science, Technology, etc.) by providing status updates, presenting data-driven recommendations, and supporting user-acceptance testing and production rollouts.
Create clear, meaningful visualizations to tell a story from data and simplify complex technical concepts for diverse audiences.
Act as a resource for other team members, providing informal guidance and fostering collaboration across teams.
Experience:
4+ years of relevant working experience in data science, data engineering, or advanced analytics.
Demonstrated track record of working independently on projects from conception to execution.
Strong project management skills, including the ability to prioritize multiple assignments and manage stakeholder expectations.
Technical Skills:
Core Languages: Advanced proficiency in Python, PySpark, and SQL for data manipulation, analysis, and pipeline development.
Cloud Platforms: Hands-on experience with cloud environments (AWS preferred, but experience with Azure or GCP is acceptable).
Data Visualization: Experience trending and visualizing data using tools such as Tableau, Power BI, or similar frameworks.
Soft Skills & Problem Solving:
Communication: Excellent verbal and written communication skills with a strong ability to explain complex data insights and build consensus among stakeholders.
Problem-Solving: Strong analytical mindset capable of taking a new perspective on existing solutions and exercising sound judgment based on data analysis.
Education:
Bachelor’s degree or equivalent experience in Data Science, Computer Science, Statistics, Mathematics, or a related quantitative field.

Employment type
Full-time

Work arrangement
Hybrid