Data Scientist - AI Labs

IDFC FIRST Bank; Mumbai; On-site; INR 1,800,000 - 2,600,000; Full time

Job summary

IDFC FIRST Bank is seeking a Data Scientist in Mumbai or Bengaluru to apply ML and NLP techniques to extract insights from structured and unstructured data. You will build predictive models, perform text analytics, and collaborate with ML engineers to deploy AI solutions.

Role emphasizes NLP, large language models, data visualization, and cross-functional collaboration. A strong foundation in Python or R and experience with ML libraries is required.

Qualifications

• 3+ years of data science and ML experience, including NLP projects.
• Strong programming skills in Python or R.
• Experience with NLP/text analytics and model deployment.

Responsibilities

• Develop predictive models using Python/R and ML libraries.
• Apply ML algorithms and statistical modeling to business problems.
• Utilize NLP frameworks for topic modelling, sentiment analysis, and text classification.
• Work with transformer models (BERT, GPT) for language tasks.
• Query/manage data with SQL/NoSQL databases.
• Create data visualizations to communicate insights.

Skills

Python

R

NLP techniques

Cross-functional teamwork

Education

Bachelor's degree in Computer Science

Bachelor's degree in Statistics

Bachelor's degree in Mathematics

Bachelor's degree in Engineering

Bachelor's degree in Data Science

Postgraduate Degree in Data Science

Postgraduate Degree in Machine Learning

Postgraduate Degree in Artificial Intelligence

Postgraduate Degree in Applied Statistics

Tools

pandas

NumPy

Scikit-learn

TensorFlow

PyTorch

Keras

NLTK

SpaCy

Gensim

Job description

Job Description:

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.

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.

Education

• Bachelor’s Degreein:
• Computer Science
• Statistics
• Mathematics
• Engineering
• Data Science
• Postgraduate Degree(preferred) in:
• Data Science
• Machine Learning
• Artificial Intelligence
• Applied Statistics

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.