Job Description

The Senior Data Analyst will play a critical role in driving the organization’s data-driven decision-making by applying advanced analytical methods across descriptive, diagnostic, and inferential analytics. This position requires not only technical expertise in statistical analysis and hypothesis testing but also the ability to synthesize insights that guide strategy, operational improvements, and product development.

Beyond individual analysis, the Senior Data Analyst will oversee the day-to-day work of the data analytics team, ensuring quality, consistency, and timeliness of outputs. The role will also serve as a key collaborator with engineering to align data infrastructure with analytics requirements, while maintaining clear documentation and supporting algorithm development efforts to strengthen the company’s core models.

Key Responsibilities

Perform advanced data analyses, including (a) descriptive analytics to summarize historical data, (b) diagnostic analytics to investigate drivers, correlations, and causes, and (c) inferential analytics to test hypotheses and assess statistical significance
Supervise and guide Data Analysts and junior team members in daily operations
Support algorithm development by providing rigorous statistical analysis and validation
Ensure data reports, dashboards, and outputs are delivered with high quality and within deadlines
Maintain, update, and create documentation of analytics processes to ensure business continuity
Collaborate with the engineering team to align infrastructure builds, pipelines, and maintenance with analytics needs

Technical Skills and Tools/Systems/Software Proficiencies

Core Analytics & Statistics

Statistical modeling (hypothesis testing, regression, correlation, ANOVA, time-series analysis)
Experimental design & inferential statistics (A/B testing, sampling methods)
Data storytelling and visualization best practices

Programming & Querying

SQL (advanced querying, optimization, joins, window functions)
Python (pandas, NumPy, SciPy, statsmodels, scikit-learn for light ML)
R (optional, but valued for advanced statistical analysis)

Data Visualization & Reporting Tools

BI/dashboarding tools: Power BI, Tableau, Looker, or equivalent
Advanced Excel/Google Sheets (pivot tables, complex formulas, VBA/macros a plus)
Data storytelling frameworks (e.g., crafting executive-level decks from analysis)

Data Infrastructure & Systems

Experience with relational databases (MySQL, PostgreSQL, MS SQL Server, Oracle)
Familiarity with data warehouses (BigQuery, Snowflake, Redshift)
Knowledge of data pipelines/ETL processes (Airflow, dbt, or equivalent)
Comfortable working with APIs for data extraction/integration

Version Control & Collaboration

Git/GitHub or GitLab for versioning analytics scripts
Jupyter Notebooks or R Markdown for reproducible analysis
Confluence/Notion/Google Docs for process documentation

Data Standards & Documentation

Familiarity with naming conventions, data quality rules, and metadata
Familiarity with documentation best practices (updating data dictionaries, documenting business rules and mappings, etc)

A Note Before You Apply

We’re building a team of rigorous thinkers who ask questions, explore patterns, and uncover insights that others might miss. If you’re someone who thrives on solving complex problems, challenging assumptions, and uncovering insights that go beyond the surface, then you’re the kind of person we want on our team.

This role isn’t about just reporting, dashboarding, or executing relayed requirements - it’s about using data to shape decisions, test hypotheses, and drive business impact. To succeed, you’ll need strong analytical skills, a quick ability to learn new contexts, and a natural curiosity to push boundaries and grow alongside a talented team.