State Street

Data Scientist - Assistant Manager

State Street · Hyderabad, Telangana, India

Financial Services · 10,001+ employees

20 h ago
Senior (5-10 yrs) Full-time India
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About the role

You will design and implement experiments and fine-tuning workflows for large language models while supporting benchmarking and performance analysis. Additionally, you will assist in data curation and documentation to enhance the company's GenAI platform.

What they look for

Python Generative AI LLM Machine Learning PyTorch TensorFlow LoRA QLoRA Data Curation Model Evaluation Anomaly Detection AWS Azure GCP MLOps RAG

Requirements

Candidates must hold a bachelor's degree in a technical field and possess 0–7 years of IT experience with at least 3 years in applied machine learning. Proficiency in Python and familiarity with ML frameworks and cloud AI services are required.

Benefits

Inclusive development opportunities Flexible work-life support Paid volunteer days Employee networks

Full description

Senior Associate – Data Scientist

About the Role

We are looking for a motivated and analytical professionals to join our GenAI Center of Excellence at State Street. This role is ideal for early-career professionals (0–7 years of experience) passionate about advancing large language model (LLM) capabilities through rigorous experimentation and applied research.

You will contribute to the development, fine-tuning, and evaluation of cutting-edge AI models, working closely with senior team members to enhance our GenAI platform.

Key Responsibilities

  • Design and implement experiments and fine-tuning workflows (e.g., LoRA, QLoRA) using Python and popular ML frameworks under the guidance of senior data scientists.
  • Support benchmarking and evaluation of LLMs, including performance analysis and anomaly detection.
  • Assist in data curation, preprocessing, and preparation for model training and evaluation.
  • Document experiment results, insights, and methodologies; maintain internal knowledge repositories.
  • Participate in model review sessions, learning and applying state-of-the-art evaluation methodologies.
  • Stay current with advances in generative models and contribute ideas to frontier model research.

Required Qualifications

  • Bachelor’s degree in Computer Science, Data Science, Statistics, Mathematics, or related technical field.
  • 0–7 years of overall experience in IT and 3+ years of experience in applied machine learning/data science (including internships or academic research).
  • Proficiency in Python programming and hands-on experience with ML frameworks such as PyTorch or TensorFlow.
  • Basic understanding of LLM architectures, fine-tuning techniques, and Python-based model training pipelines.
  • Familiarity with evaluation metrics for generative models and experience analyzing model results using Python.
  • Familiarity with cloud AI/ML services (AWS, Azure, or GCP) and MLOps practices.

Work Schedule

On-premise

Keywords

Data Scientist, Generative AI, LLM, Applied Machine Learning, RAG, Agentic Applications, Python, Azure, Model Evaluation

About State Street

Across the globe, institutional investors rely on us to help them manage risk, respond to challenges, and drive performance and profitability. We keep our clients at the heart of everything we do, and smart, engaged employees are essential to our continued success.

We are committed to fostering an environment where every employee feels valued and empowered to reach their full potential. As an essential partner in our shared success, you’ll benefit from inclusive development opportunities, flexible work-life support, paid volunteer days, and vibrant employee networks that keep you connected to what matters most. Join us in shaping the future.

As an Equal Opportunity Employer, we consider all qualified applicants for all positions without regard to race, creed, color, religion, national origin, ancestry, ethnicity, age, disability, genetic information, sex, sexual orientation, gender identity or expression, citizenship, marital status, domestic partnership or civil union status, familial status, military and veteran status, and other characteristics protected by applicable law.

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