Lead Data Scientist - Generative AI (GenAI)

Precision Inc.

3 days ago

Role details

Contract type

Permanent contract

Employment type

Full-time (> 32 hours)

Working hours

Regular working hours

Languages

English

Experience level

Senior

Job location

Remote

Tech stack

Artificial Intelligence

Amazon Web Services (AWS)

Data analysis

Azure

Big Data

Cloud Computing

Continuous Integration

Python

Machine Learning

NumPy

Performance Tuning

TensorFlow

Standard Sql

Azure

Feature Engineering

Data Ingestion

PyTorch

Retrieval-Augmented Generation

Large Language Models

Prompt Engineering

Deep Learning

Model Validation

Generative AI

Pandas

Scikit Learn

Machine Learning Operations

Databricks

Job description

We are seeking a highly accomplished Lead Data Scientist with strong Generative AI expertise to design and drive enterprise-scale AI solutions. The ideal candidate will have deep experience in machine learning, statistical modeling, Large Language Models (LLMs), and advanced analytics, along with strong leadership capabilities to guide teams and deliver impactful AI-driven products., * Define and lead GenAI and data science strategy across business use cases.

Design and implement LLM-based applications including RAG architectures.
Lead development of machine learning models and advanced analytics solutions.
Perform deep exploratory data analysis (EDA) and derive actionable insights.
Architect end-to-end ML pipelines (data ingestion * training * deployment * monitoring).
Optimize models for accuracy, scalability, and cost efficiency.
Collaborate with Data Engineers, ML Engineers, and Product stakeholders.
Establish best practices for MLOps, model governance, and evaluation frameworks.
Mentor junior data scientists and lead technical decision-making.
Drive innovation in AI/ML and Generative AI solutions.

Requirements

Data Science & ML

Strong expertise in Machine Learning & Statistical Modeling
Python (NumPy, Pandas, Scikit-learn)
Feature engineering, model evaluation, and tuning

Generative AI

LLMs (OpenAI, Anthropic, LLaMA, etc.)
Prompt engineering and LLM orchestration
RAG (Retrieval-Augmented Generation)
LangChain / LlamaIndex / Hugging Face

Data & Processing

SQL
Large-scale data handling and transformation

Cloud & MLOps

AWS / Azure / GCP
MLflow / SageMaker / Azure ML
CI/CD for ML pipelines
Model deployment and monitoring, * Experience with Deep Learning (TensorFlow / PyTorch)
Exposure to vector databases (Pinecone, FAISS, Chroma)
Experience with Databricks or big data platforms
Strong leadership, communication, and stakeholder management skills

Eligibility & Compliance