Data Science Lead (India) (Remote)

Codvo.ai; Pune District; Remote; INR 1,500,000 - 2,500,000; Full time

Job summary

A global technology services company in Pune is seeking a Senior / Lead Data Scientist with expertise in Machine Learning, Deep Learning, and Generative AI. The role involves designing, building, and optimizing ML solutions, working with time-series data, and leading small teams. Ideal candidates will have over 7 years of experience in Data Science, strong programming skills in Python, and familiarity with frameworks and tools like TensorFlow and AWS. Competitive salary and growth opportunities are offered.

Qualifications

• At least 7 years of experience in Data Science or Machine Learning roles.
• Expertise in deep learning frameworks like TensorFlow, Keras, and PyTorch.
• Hands-on experience with LLMs and GenAI technologies.

Responsibilities

• Design and deploy production-grade ML and DL models focused on time-series data.
• Build and optimize end-to-end ML pipelines.
• Implement LLM-powered applications and integrate with traditional ML systems.

Skills

Data Science

Machine Learning

Deep Learning

Python

Statistical Modeling

NLP

Time-series Modeling

GenAI

Tools

TensorFlow

Keras

PyTorch

SQL

NoSQL

REST APIs

AWS

GCP

Azure

Big Data tools

Job description

Company Overview

At Codvo, software and people transformations go hand-in-hand. We are a global empathy-led technology services company where product innovation and mature software engineering are part of our core DNA. Respect, Fairness, Growth, Agility, and Inclusiveness are the core values we aspire to live by every day.

We continue to expand our digital strategy, architecture, AI/ML, GenAI, and product engineering capabilities to deliver outside-the-box thinking and measurable business outcomes for our clients.

Role Overview

We are looking for a Senior / Lead Data Scientist with strong expertise in Machine Learning, Deep Learning, and production-grade ML systems, particularly around time-series data, forecasting, and predictive modeling, along with hands-on experience in Generative AI (LLMs), Retrieval-Augmented Generation (RAG), and Agentic AI systems.

This role requires someone who can design, build, optimize, and productionize ML and GenAI solutions end-to-end, work closely with data engineering teams, and take ownership of complex AI workflows. Prior experience leading small teams or mentoring junior data scientists is strongly preferred.

Key Responsibilities

Core ML & Predictive Analytics

• Design, develop, and deploy production-grade ML and DL models with a focus on time-series data, forecasting, and predictive analytics.
• Build and optimize end-to-end ML pipelines, from data preprocessing and feature engineering to model training, evaluation, deployment, and monitoring.
• Apply advanced ML techniques including regression, tree-based models, ensemble methods, deep learning, and optimization algorithms.
• Perform feature extraction and dimensionality reduction using techniques such as autoencoders for high-dimensional datasets.
• Track experiments, model performance, and metrics using industry-standard tools and best practices.

GenAI, LLMs & Agentic AI

• Design and implement LLM-powered applications, including Retrieval-Augmented Generation (RAG) systems for enterprise use cases such as analytics automation, knowledge assistants, and decision-support tools.
• Build document ingestion, chunking, embedding, and retrieval pipelines for structured and unstructured data using vector databases.
• Develop Agentic AI workflows that enable multi-step reasoning, tool usage, and autonomous task execution.
• Integrate LLMs with traditional ML systems to enhance explainability, insights generation, and user interaction.
• Implement guardrails and evaluation mechanisms to reduce hallucinations and ensure reliable, grounded LLM outputs.
• Optimize LLM inference for latency, cost, and scalability in cloud and hybrid environments.

Required Skills – Technical

• 7+ years of hands-on experience in Data Science, Machine Learning, or Applied AI roles.
• Strong foundation in statistical modeling and machine learning, including:
  • Regression, boosting trees, random forests
  • Time-series modeling and forecasting
  • Optimization techniques (linear, nonlinear, stochastic)
• Deep Learning expertiseusing frameworks such as:
  • TensorFlow, Keras, PyTorch
  • Experience with RNN, LSTM, GRU, CNN is a plus
• Experience with NLP and unstructured data processing.
• Hands-on experience with LLMs and GenAI, including:
  • Retrieval-Augmented Generation (RAG)
  • Vector databases (FAISS, Chroma, Pinecone, or similar)
  • Prompt engineering and LLM evaluation
  • Agentic AI frameworks (e.g., LangChain, LangGraph, or similar)
• Strong programming skills in Python (R is a plus); familiarity with sh/bash scripting.
• Experience working with SQL and NoSQL databases.
• Experience building and consuming REST APIs and web services.
• Exposure to Big Data tools (Spark, Hadoop, or similar) is a strong plus.
• Cloud experience (AWS / GCP / Azure); exposure to GenAI platforms (AWS Bedrock, Azure OpenAI, Vertex AI) is a plus.