PharmEasy - Manager/Lead - Analytics

Manager/Lead Analytics

Job Summary :

We are looking for a seasoned analytics leader to drive data-driven decision-making across our organization. In this role, you will own the analytics agenda for one or more business verticals, acting as a strategic thought partner to senior business and product stakeholders while leading a high-performing team of analysts and data scientists. The ideal candidate combines deep technical expertise in machine learning, statistical modelling, and Insights Frameworks with the ability to translate ambiguous business problems into structured, impactful solutions and the leadership presence to scale those solutions across the organization.
Key Responsibilities :
Business Partnering :
- Serve as the primary analytics partner to senior business and product leaders, proactively identifying opportunities where data can drive measurable business outcomes.
- Translate complex, ambiguous business problems into well-scoped analytics roadmaps with clear milestones, success metrics, and ROI framing.
- Influence strategic decisions by presenting data-backed recommendations to senior stakeholders, including cross-functional leadership.
- Build strong, trust-based relationships across functions (Growth, Product, Engineering) to embed analytics into core business workflows and planning cycles.
- Drive a culture of experimentation and data literacy across business teams; design and interpret A/B tests and other causal inference frameworks to validate hypotheses.
Team Management & Leadership :

- Lead, mentor, and develop a team of 5 - 8 analysts and data scientists, fostering a high-performance, collaborative culture.
- Define team goals, manage performance, and provide structured career development pathways for team members.
- Oversee project portfolio management - prioritize competing demands, allocate resources effectively, and ensure on-time delivery against business commitments.
- Champion best practices in analytics engineering, code review, documentation, and knowledge sharing within the team.
- Recruit and onboard top analytics talent to grow team capability in line with business needs.
Technical Execution :
- Architect and oversee end-to-end analytics solutions - from data ingestion and wrangling through modelling, validation, and production deployment.
- Lead the development of advanced ML and statistical models (regression, classification, clustering, time series, causal inference, NLP, recommendation systems) to solve high-stakes business problems.
- Hands-on proficiency in Python (pandas, scikit-learn, XGBoost, PyTorch/TensorFlow) and SQL (complex joins, window functions, query optimization across large datasets).
- Design scalable data models and pipelines; experience with cloud data platforms (e.g., BigQuery, Snowflake, Redshift) and orchestration tools (e.g., Airflow, dbt) is a strong plus.
- Build and maintain executive-grade dashboards and reporting frameworks using BI tools (Tableau, Power BI, Metabase) that serve as single sources of truth for business KPIs.
- Ensure rigorous standards for data quality, validation, and model monitoring in production environments.
- Evaluate and adopt emerging tools and methodologies (e.g., LLM-powered analytics, AutoML, feature stores) to continuously raise the team's capability bar.
Qualifications Required :
- 6+ years of experience in analytics, data science, or a related quantitative field, with at least 2 years in a team lead or people management role.
- Bachelor's or Master's degree in Engineering, Statistics, Applied Mathematics, Computer Science, Data Science, or a related quantitative discipline.
- Demonstrated expertise in Python and SQL for data wrangling, complex analysis, and building and deploying ML models.
- Strong command of statistical foundations : hypothesis testing, regression analysis, Bayesian inference, and common ML algorithms.
- Proven track record of deploying analytics and ML solutions in production and demonstrating measurable business impact.
- Experience managing and growing teams of 5+ members, with a structured approach to performance management and mentorship.
- Excellent communication and stakeholder management skills - able to distill technical complexity into clear narratives for senior, non-technical audiences.
Preferred :
- Master's degree in Data Science, Business Analytics, or a related quantitative field.
- Hands-on experience with cloud data platforms (BigQuery, Hive, Redshift) and data pipeline tools (dbt, Airflow).
- Familiarity with causal inference methods (diff-in-diff, propensity score matching, synthetic control) and experimentation frameworks.
- Experience in a B2C e-commerce or consumer technology environment.
- Exposure to LLMs, generative AI tooling, or MLOps practices.
Why Join Us :
- Shape the analytics strategy for a fast-growing organization, with direct influence on business outcomes.
- Lead a talented, ambitious team and invest in their long-term growth.
- Work at the intersection of deep technical practice and senior business leadership.
- Competitive compensation, including performance-linked incentives and comprehensive benefits.