Require a Data Scientist in Mumbai

Key Responsibilities:

• Data Analysis & Insights: Analyze large datasets from multiple sources (clickstream sales user engagement) to uncover insights and support business decision-making.
  

• Machine Learning: Develop deploy and maintain machine learning models for recommendations personalization customer segmentation demand forecasting and pricing.
  

• A/B Testing: Design and analyze A/B tests to evaluate the performance of product features marketing campaigns and user experiences.
  

• Data Pipeline Development: Work closely with data engineering teams to ensure the availability of accurate and timely data for analysis.
  

• Collaborate with Cross-functional Teams: Partner with product marketing and engineering teams to deliver actionable insights and improve platform performance.
  

• Data Visualization: Build dashboards and visualizations to communicate findings to stakeholders in an understandable and impactful way.
  

• Exploratory Analysis: Identify trends patterns and outliers to help guide business strategy and performance improvements.
  

• Proficiency in Python or R: Experience in using Python or R for data analysis and machine learning.
  

• SQL: Strong SQL skills to query and manipulate large datasets.
  

• Machine Learning Frameworks: Familiarity with libraries such as Scikit-learn TensorFlow or PyTorch.
  

• Data Wrangling: Ability to clean organize and manipulate data from various sources.
  

• A/B Testing: Experience designing experiments and interpreting test results.
  

• Visualization Tools: Proficiency with data visualization tools (e.g. Tableau Power BI Matplotlib Seaborn).
  

• Statistics & Probability: Strong grasp of statistical methods hypothesis testing and probability theory.
  

• Communication: Ability to convey complex findings in clear simple terms for non-technical stakeholders.
  

• E-commerce Experience: Experience working with e-commerce datasets (e.g. user behavior transaction data inventory and product data).
  

• Experience with Big Data: Familiarity with big data technologies (e.g. Hadoop Spark BigQuery).
  

• Cloud Platforms: Experience with cloud platforms like AWS GCP or Azure for data storage and model deployment.
  

• Business Acumen: Understanding of key business metrics in e-commerce such as conversion rates LTV and customer acquisition cost (CAC).
  

• Bachelors or Masters degree in Data Science Computer Science Mathematics Statistics or related field.