Data Scientist

LTM; Mumbai; On-site; INR 800,000 - 1,200,000; Full time

Job summary

A technology solutions company in Mumbai is looking for a Data Scientist to join its team. The ideal candidate will have a strong background in machine learning and natural language processing, capable of developing scalable AI/ML solutions for complex business challenges. Responsibilities include designing machine learning models, collaborating with cross-functional teams, and ensuring model performance. Key skills required are proficiency in Python and experience with machine learning algorithms, specifically for financial datasets.

Qualifications

• Strong foundation in machine learning, NLP, and data engineering.
• Ability to build scalable AI/ML solutions for complex business problems.
• Experience in deploying machine learning models for structured and unstructured data.

Responsibilities

• Design and develop machine learning models for diverse projects.
• Collaborate with teams to translate business requirements into data science solutions.
• Ensure model interpretability and monitor performance for continuous improvement.

Skills

Python proficiency

Machine learning algorithms

Natural Language Processing (NLP)

Experience with LLMs

SQL experience

Data preprocessing

Hands-on experience with TensorFlow

Tools

pandas

scikit-learn

NumPy

PyTorch

TensorFlow

SQL

Docker

Kubernetes

Job description

Mandatory Certification DASCA Big Data Senior Data Scientist OR Databricks Certified Data Scientist Professional OR Microsoft Certified Azure Data Scientist Associate

Job Summary

We are seeking a highly motivated and skilled Data Scientist to join our growing team. The ideal candidate will have a strong foundation in machine learning, natural language processing (NLP), and data engineering with the ability to build scalable AI/ML solutions for complex business problems. You will work on diverse projects including anomaly detection in financial datasets and building GenAI-powered conversational systems.

Key Responsibilities

• Design, develop, and deploy machine learning models for structured and unstructured data.
• Build and fine‑tune NLP pipelines for document understanding and conversational AI.
• Perform anomaly detection and pattern recognition in large‑scale financial datasets.
• Collaborate with cross‑functional teams, including product managers, domain experts, and engineers.
• Translate business requirements into data science solutions and present findings to stakeholders.
• Ensure model interpretability, performance monitoring, and continuous improvement.
• Stay updated with the latest advancements in AI/ML and GenAI technologies such as Agentic AI.

Primary Skills (Must Have)

• Proficiency in Python and libraries such as pandas, scikit‑learn, NumPy, PyTorch, TensorFlow.
• Strong understanding of machine learning algorithms, especially for classification, regression, and clustering.
• Experience with Natural Language Processing (NLP), transformers, embeddings, text classification, summarization.
• Familiarity with LLMs, Large Language Models, and frameworks like LangChain, Hugging Face Transformers, OpenAI APIs.
• Knowledge of vector databases such as FAISS, Pinecone, Weaviate and retrieval‑augmented generation (RAG).
• Experience with data preprocessing, exploratory data analysis, feature engineering, and model evaluation techniques.
• Hands‑on experience with SQL and working with large datasets.

Secondary Skills (Nice to Have)

• Exposure to Devin tool for coding tasks.
• Experience with cloud platforms (AWS, Azure, GCP) and MLOps tools such as MLflow, DVC, Airflow.
• Familiarity with financial data and regulatory reporting (e.g., FRB filings, 14Q, 9C).
• Exposure to Docker, Kubernetes, and API development for model deployment.

Good to Have

• Experience with time‑series analysis and graph‑based models.
• Understanding of data privacy, model fairness, and explainability.
• Contributions to open‑source projects or published research papers.

Communication & Behavioral Skills

• Strong verbal and written communication skills to explain technical concepts to non‑technical stakeholders.
• Ability to collaborate effectively in a team environment and work independently when needed.
• Demonstrated problem‑solving mindset and curiosity to explore new technologies.
• High level of accountability, ownership, and attention to detail.
• Comfortable working in an agile, fast‑paced environment with shifting priorities.