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.

Requirements

- 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 transparent 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.

Required Skills:

Career in software testing

Required Education:

(CSE IT)

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