Data Scientists

Axsyntra; India; On-site; INR 800,000 - 1,200,000; Full time

Job summary

A leading data analytics company in India is seeking a Data Scientist passionate about transforming raw data into actionable insights. This role involves designing data-driven solutions, collaborating with diverse teams, and applying advanced analytics to build predictive models. Ideal candidates will have proficiency in Python or R, a strong grasp of statistics, and experience with data visualization tools. Join us to help drive effective and innovative data solutions.

Qualifications

• Proficiency in Python or R.
• Strong foundation in statistics, probability, and machine learning.
• Experience with data visualization tools.

Responsibilities

• Collect, clean, and analyze large datasets to identify trends.
• Build, test, and deploy machine learning and AI models.
• Design and select impactful features for models.

Skills

Python (NumPy, pandas, scikit-learn)

Statistics and probability

Data visualization tools (Matplotlib, Plotly, Tableau, Power BI)

SQL and database management

Job description

We are seeking a Data Scientist to work on high-impact projects that turn raw data into actionable insights. You will play a key role in designing data-driven solutions, applying advanced analytics, and building predictive models to support business decisions and AI-powered products. Working alongside engineers, analysts, and domain experts, you’ll ensure data is used effectively, responsibly, and innovatively to solve complex challenges.

Required Skills & Experience

• Proficiency in Python (NumPy, pandas, scikit-learn, etc.) or R.
• Strong foundation in statistics, probability, and machine learning.
• Experience with data visualization tools (Matplotlib, Plotly, Tableau, Power BI).
• Understanding of SQL and database management.

Key Responsibilities

• Data Exploration & Analysis – Collect, clean, and analyze large datasets to identify trends, patterns, and correlations.
• Model Development – Build, test, and deploy statistical, machine learning, and AI models for various use cases.
• Feature Engineering – Design and select impactful features to improve model performance.

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