Data Scientist - AI Labs

Job Requirements

About the Role

The Data Scientist will be part of the Data & Analytics team, based in Mumbai or Bangalore.

This role focuses on applying machine learning and statistical techniques to extract meaningful insights from structured and unstructured data. You will be responsible for developing predictive models, conducting text analytics, and collaborating with ML engineers to ensure successful deployment and performance of AI solutions. A strong foundation in NLP and experience with large language models will be highly valuable.

Key Responsibilities:

Primary Responsibilities

• Develop predictive models using Python or R and data science libraries such as pandas, NumPy, Scikit-learn, TensorFlow, PyTorch, or Keras.
• Apply machine learning algorithms and statistical modeling techniques to solve business problems.
• Utilize NLP libraries and frameworks (e.g., NLTK, SpaCy, Gensim) for text analytics tasks such as topic modeling, sentiment analysis, and text classification.
• Work with transformer models like BERT and GPT for advanced language understanding.
• Query and manage data using SQL and NoSQL databases.
• Create data visualizations using tools like Matplotlib, Seaborn, or Tableau to communicate insights effectively.

Secondary Responsibilities

• Participate in multiple data analysis projects, with a focus on text analytics and natural language understanding.
• Build, validate, and deploy predictive models based on large text datasets.
• Clean and preprocess text data for machine learning tasks.
• Collaborate with ML engineers to ensure smooth deployment and integration of models.

What We Are Looking For :

Education

Postgraduate Degree or bachelor’s degree in: Computer Science, Economics, Statistics, Mathematics, Engineering, computational science

Experience

3+ years of relevant experience in data science and machine learning, ideally with exposure to NLP and text analytics projects.

Skills And Attributes

• Strong programming skills in Python or R.
• Deep understanding of machine learning and NLP techniques.
• Experience with large-scale data processing and model deployment.
• Ability to work collaboratively in cross-functional teams.
• Strong analytical thinking and problem-solving abilities.

Key Success Metrics

• Timely and error-free delivery of data science solutions.
• Effective identification and resolution of training infrastructure issues.
• Technical leadership in analytics and model development projects.