Process Manager
eClerx · Mumbai, Maharashtra, India
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eClerx · Mumbai, Maharashtra, India
Job Description Job Summary We are looking for a Senior Analytics professional with strong expertise in SQL, Python, and data analytics to drive business insights, reporting, and data-driven decision-making. The ideal candidate should have experience working with large datasets, building analytical solutions, and collaborating with business stakeholders, preferably within the eCommerce, Retail, or Digital business domain. Key Responsibilities • Analyze large and complex datasets to identify trends, patterns, and business opportunities. • Develop dashboards, reports, and KPIs to support business decision-making. • Write optimized SQL queries for data extraction, transformation, and analysis. • Utilize Python for data manipulation, statistical analysis, automation, and predictive modeling. • Partner with business teams to understand requirements and translate them into analytical solutions. • Perform ad-hoc analysis and present actionable insights to stakeholders. • Build and maintain data pipelines and analytical frameworks. • Monitor business performance and recommend improvements based on data insights. • Collaborate with Data Engineering and Product teams to enhance data quality and accessibility. Required Skills • Strong proficiency in SQL (Joins, CTEs, Window Functions, Query Optimization). • Hands-on experience with Python (Pandas, NumPy, Matplotlib, Scikit-learn). • Experience with BI and visualization tools such as Tableau, Power BI, or Looker. • Strong understanding of statistics, experimentation, and data analysis techniques. • Experience working with cloud platforms such as AWS, GCP, or Azure. • Excellent problem-solving and stakeholder management skills. Preferred Skills • Experience in eCommerce, Retail, Marketplace, or Digital Analytics. • Knowledge of customer analytics, marketing analytics, pricing analytics, or product analytics. • Exposure to machine learning and predictive analytics. • Experience with ETL processes and data warehousing concepts.