Data Scientist - I

Purplle.com; Mumbai; On-site; INR 800,000 - 1,500,000; Full time

Job summary

Purplle.com in Mumbai is seeking a Data Scientist with expertise in data analysis, machine learning, and A/B testing. The ideal candidate will have proficiency in Python or R, strong SQL skills, and experience with machine learning frameworks. Responsibilities include analyzing datasets, developing machine learning models, and collaborating with cross-functional teams to deliver actionable insights. Candidates should hold a Bachelor’s or Master’s degree in a relevant field and have familiarity with visualization tools and big data technologies.

Qualifications

• Experience using Python or R for data analysis and machine learning.
• Strong SQL skills to query and manipulate large datasets.
• Familiar with libraries such as Scikit-learn, TensorFlow, or PyTorch.
• Ability to clean, organize, and manipulate data from various sources.
• Experience designing experiments and interpreting test results.
• Proficiency with data visualization tools.
• Strong grasp of statistical methods, hypothesis testing, and probability theory.
• Ability to convey complex findings in clear terms.

Responsibilities

• Analyze large datasets from multiple sources to support business decision-making.
• Develop, deploy, and maintain machine learning models.
• Design and analyze A/B tests for product features and marketing campaigns.
• Work with data engineering teams for accurate and timely data.
• Collaborate with product, marketing, and engineering teams.
• Build dashboards and visualizations for stakeholders.
• Identify trends and patterns to guide business strategy.

Skills

Proficiency in Python or R

SQL

Machine Learning Frameworks

Data Wrangling

A/B Testing

Visualization Tools

Statistics & Probability

Communication

Education

Bachelor’s or Master’s degree in Data Science, Computer Science, Mathematics, Statistics, or related field

Tools

Tableau

Power BI

Matplotlib

Seaborn

Hadoop

Spark

BigQuery

AWS

GCP

Azure

Job description

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.

Required Skills

• 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.

Preferred Qualifications

• 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).

Education

• Bachelor’s or Master’s degree in Data Science, Computer Science, Mathematics, Statistics, or related field.