Require a Data Scientist in Mumbai

TestHiring; Mumbai; On-site; INR 1,200,000 - 2,500,000; Full time

Job summary

TestHiring is a data-driven online candidate evaluation platform empowering recruiters with unbiased scoring and fast insights. The role focuses on analyzing large datasets, building ML models for recommendations, and delivering actionable dashboards to stakeholders.

Responsibilities include designing experiments, collaborating with cross-functional teams, and communicating complex findings in clear terms to non-technical stakeholders.

Qualifications

• Proficiency in Python or R for data analysis and ML.
• Strong SQL skills to query large datasets.
• Familiarity with ML libraries such as Scikit-learn, TensorFlow, or PyTorch.
• Data wrangling and cleaning across diverse data sources.
• Experience designing and analyzing A/B tests.
• Proficiency with visualization tools like Tableau/Power BI.

Responsibilities

• Analyze large datasets from multiple sources to uncover insights and support business decisions.
• Develop, deploy, and maintain ML models for recommendations, personalization, segmentation, demand forecasting, and pricing.
• Design and analyze A/B tests to evaluate product features and campaigns.
• Collaborate with data engineering to ensure availability of accurate data for analysis.
• Partner with product, marketing, and engineering to deliver actionable insights and improve platform performance.
• Build dashboards and visualizations to communicate findings to stakeholders.
• Identify trends, patterns, and outliers to guide strategy and performance improvements.

Skills

Data Analysis & Insights

A/B Testing

Data Visualization

Exploratory Analysis

Statistics & Probability

Machine Learning

Communication

Business Acumen

ML in e-commerce

Education

Bachelor’s or Master’s degree in Data Science/CS/Math/Statistics

Tools

Python

R

Scikit-learn

TensorFlow

PyTorch

Tableau

Power BI

Matplotlib

Seaborn

Hadoop

Spark

BigQuery

AWS

GCP

Azure

Job description

TestHiring is a smart online candidate evaluation platform designed for recruiters, HR teams, and hiring managers seeking efficiency, fairness, and accuracy in their hiring. With early screening via automated ranking and unbiased scoring, TestHiring helps identify top talent in less time

Join us at TestHiring to revolutionize how your hiring works—faster, fairer, and more cost-effective. Discover more on our Product, Features, and Resources pages, or explore our Blog for insights on skills-based recruitment.

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.

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 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).

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