Description
We are seeking a Lead Product Analyst to join our operations team in Hyderabad, India. As a Lead Product Analyst, you will partner with our operational teams to drive data-driven decisions that support our fast-growing product. You will focus on building and refining analytical models for strategic capacity planning, take ownership of data pipelines, develop predictive models, and provide critical insights to assess operational health.
Key responsibilities:
- Analytical Capacity Planning and Forecasting: Build and refine analytical models for strategic capacity planning and forecasting efforts.
- Data Pipeline Ownership: Maintain and improve data flow, ensuring reliability and accuracy.
- Predictive Modeling and Cause and Effect Analysis: Develop and implement robust models to predict outcomes and identify key drivers.
- Strategic Support and Analysis: Provide critical insights to assess operational health and conduct in-depth cost analysis.
- Performance Tracking and Initiative Optimisation: Monitor and track performance of key strategic initiatives.
- KPI Implementation and Target Setting: Lead development and implementation of operations KPI tree and target-setting framework.
- Stakeholder Collaboration and Process Standardisation: Collaborate with stakeholders to standardise processes across forecasting, scheduling, and real-time operations.
Requirements:
- 6-8 years of experience in analytics with a demonstrated ability to approach complex problems with a systems mindset.
- Strong quantitative and statistical background, comfortable with probability, hypothesis testing, regression, time series analysis, and thinking in terms of models and trade-offs.
- Experience with operational analytics, efficiency analysis, cost modelling, performance measurement, or process optimisation.
- Experience with complex data models in SQL and advanced analysis using Python/R.
- Ability to tell a story with data and proactively guide strategy based on insights.
Nice to have:
- Experience with optimisation problems such as queuing theory, scheduling, or resource allocation.
- Familiarity with forecasting techniques.
- Experience building data foundations that support ML/AI.
- Prior experience in operations, servicing, or compliance domains.