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Salary
≈ $20k – $49k per year (Estimated)
Location
In office (Hyderabad)
Seniority
Middle · 3+ years exp
Employment
Full-Time

Confirmed on the employer's own hiring board on Oct 27, 2026. First seen by Alion on Oct 26, 2026. Workday scores A on the Alion truth index.

Overview
Company
Impact
Profile match
Workday is a leading American cloud software provider specializing in enterprise applications for human capital management, financial planning, and business operations. Headquartered in Pleasanton, California, the company delivers integrated platforms that streamline workforce administration, payroll, talent acquisition, and analytics for thousands of global organizations. Founded in 2005, it powers an expansive recruiting and implementation infrastructure that enables enterprises to configure, test, and deploy customized career portals and automated hiring workflows.

FactSet creates flexible, open data and software solutions for over 200,000 investment professionals worldwide, providing instant access to financial data and analytics that investors use to make crucial decisions.

At FactSet, our values are the foundation of everything we do. They express how we act and operate, serve as a compass in our decision-making, and play a big rolein how we treat each other, our clients, and our communities. We believe that the best ideas can come from anyone, anywhere, at any time, and that curiosity is the key to anticipatingour clients’ needs and exceeding their expectations.

Your Team's Impact

We’re seeking a passionate and experienced Senior Python & Machine Learning Engineer to join our Data domain team. You’ll work on unique, one-of-a-kind problem statements using advanced GenAI, large language models (LLMs), and modern data engineering frameworks. You will help conceptualize and deliver impactful solutions that push the boundaries of data science and machine learning in finance.

What You'll Do :

  • Design, develop, and deploy sophisticated machine learning and GenAI models to solve complex data problems at scale.
  • Implement, optimize, and scale ML solutions using Databricks, Spark, and cloud-native data ecosystems (AWS/Azure/GCP).
  • Collaborate with other engineers, product managers, and UX teams to build robust, high-performance Python-based analytics pipelines.
  • Develop and finetune LLMs and generative AI applications for structured and unstructured financial data.
  • Architect data processing workflows leveraging Delta Lake, Feature Stores, and MLOps best practices.
  • Translate cutting-edge research (papers, new ML techniques) into production solutions.
  • Mentor junior data scientists and engineers on ML, best practices and GenAI.
  • Work on one-of-a-kind data challenges, including entity disambiguation, real-time risk analytics, NLP, graph data modeling, and anomaly detection.
  • Keep up-to-date with the latest in ML tooling, GenAI, Databricks, and cloud data infrastructure.

What We're Looking For

  • Bachelor’s/Master’s in Computer Science, Engineering, or related field.
  • 3-5 years professional experience in ML, Python programming, and data engineering.
  • Deep expertise in Python (NumPy, Pandas, PySpark, FastAPI, etc.) and ML frameworks (TensorFlow, PyTorch, Transformers).
  • Practical experience with GenAI: training/fine-tuning LLMs (OpenAI, HuggingFace, Google Gemini, etc.), prompt engineering, and retrieval-augmented generation (RAG).
  • Hands-on experience with Databricks (Workspace, MLflow, Delta Lake, Notebooks).
  • Strong knowledge of cloud data platforms (AWS, Azure, GCP) and containerization (Docker, Kubernetes).
  • Applied experience with ETL/ELT, data lakes, real-time streaming (Kafka, Spark Streaming).
  • Proven track record of tackling cutting-edge data problems at scale - published research or open source contributions a plus.
  • Familiarity with modern MLOps toolchains (MLflow, Airflow, Feature Store, CI/CD).
  • Effective communicator with excellent collaboration skills.

Tech Stack:

  • Python, PySpark, FastAPI, Flask
  • TensorFlow, PyTorch, HuggingFace Transformers
  • Databricks, Delta Lake, MLflow
  • AWS/Azure/GCP - S3, Blob Storage, EC2, Lambda, Step Functions
  • SQL, NoSQL

What's In It For You

At FactSet, our people are our greatest asset, and our culture is our biggest competitive advantage. Being a FactSetter means:

  • The opportunity to join an S&P 500 company with over 45 years of sustainable growth powered by the entrepreneurial spirit of a start-up.
  • Support for your total well-being. This includes health, life, and disability insurance, as well as retirement savings plans and a discounted employee stock purchase program, plus paid time off for holidays, family leave, and company-wide wellness days.
  • Flexible work accommodations. We value work/life harmony and offer our employees a range of accommodations to help them achieve success both at work and in their personal lives.
  • A global community dedicated to volunteerism and sustainability, where collaboration is always encouraged, and individuality drives solutions.
  • Career progression planning with dedicated time each month for learning and development.

Company Overview:

FactSet (NYSE:FDS| NASDAQ:FDS) helps the financial community to see more, think bigger, and work better. Our digital platform and enterprise solutions deliver financial data, analytics, and open technology to more than 8,200 global clients, including over 200,000 individual users. Clients across the buy-side and sell-side, as well as wealth managers, private equity firms, and corporations, achieve more every day with our comprehensive and connected content, flexible next-generation workflow solutions, and client-centric specialized support. As a member of the S&P 500, we are committed to sustainable growth and have been recognized among the Best Places to Work in 2023 by Glassdoor as a Glassdoor Employees’ Choice Award winner. Learn more at www.factset.com and follow us on X and LinkedIn.

At FactSet, we celebrate difference of thought, experience, and perspective. Qualified applicants will be considered for employment without regard to characteristics protected by law.

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