Senior Data Analyst, for Business
Há 6 dias
About The Role
The Uber for Business (U4B) Analytics and Insights team supports the business by delivering data driven solutions that guide strategic decisions across sales, operations, and growth initiatives. We develop impactful dashboards, monitor key KPIs, and build machine learning models such as regression models to estimate Full Potential and share of wallet, that help scale insights and streamline decision making processes. As part of the team, the candidate would directly contribute to the business by applying advanced analytics, ML models, and AI to uncover deeper insights and enable scalable, tech-forward solutions.
What You'll Do
- Build and maintain dashboards and reports to track key business and sales KPIs, ensuring data accuracy and timely delivery.
- Develop, test, and maintain machine learning models (e.g., regression models) to estimate Full Potential and share of wallet.
- Partner with cross-functional teams (e.g., Sales, Strategy, Operations) to translate business questions into analytical projects.
- Automate data pipelines and reporting workflows to improve efficiency and scalability using SQL, Python, and cloud tools.
- Analyze trends, identify growth opportunities, and present actionable insights to stakeholders to support strategic decision-making.
What You'll Need
- A minimum of 4-5 years of experience in a similar role (e.g. BI Analyst, BI Engineer, Data Scientist, Data engineer, Data Analyst, Business Intelligence Engineer, etc.)
- Strong proficiency in SQL and Python: Hands-on experience in data manipulation, KPI tracking, and building scalable data workflows.
- Experience developing machine learning models: Regression models used for business forecasting, share of wallet estimation, and opportunity sizing.
- Proven ability to build and maintain dashboards and reports: Support cross-functional stakeholders with clear, actionable insights through Tableau
- Experience deploying and operationalizing ML models: Including model monitoring, performance tuning, and integration into business workflows (e.g., via Flask, MLflow, or cloud services)
- Advanced statistical knowledge: with expertise in techniques like multivariate regression, time series analysis, and A/B testing to drive data-backed strategy.
- Strong business acumen: Ability to translate complex analytical findings into strategic recommendations, especially in sales performance and market share contexts.
- Cloud platform experience (GCP, AWS, or Azure): Particularly working with data warehouses like BigQuery or Snowflake to scale data processing and model training.
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