3 days ago
Hyderābād, IndiaSenior
Responsibilities
- Design, develop, deploy, optimize, and scale machine learning and GenAI models for complex financial data problems.
- Build Python-based analytics pipelines and production data processing workflows using Databricks, Spark, Delta Lake, and Feature Stores.
- Develop and fine-tune LLMs and generative AI applications, including prompt engineering and retrieval-augmented generation.
- Create solutions for entity disambiguation, real-time risk analytics, NLP, graph data modeling, and anomaly detection.
- Translate ML research and new techniques into production solutions.
- Mentor junior data scientists and engineers on machine learning, GenAI, and engineering best practices.
- Collaborate with engineers, product managers, and UX teams on high-performance analytics solutions.
Requirements
- Bachelor’s or Master’s degree in Computer Science, Data Science, Mathematics, or a related field.
- 3–5 years of professional experience in machine learning, Python programming, and data engineering.
- Deep Python expertise, including NumPy, Pandas, PySpark, and related frameworks such as FastAPI.
- Experience with TensorFlow, PyTorch, and HuggingFace Transformers.
- Practical experience training or fine-tuning LLMs and using OpenAI, HuggingFace, or Google Gemini technologies.
- Experience with prompt engineering, retrieval-augmented generation, and generative AI applications.
- Hands-on experience with Databricks Workspace, MLflow, Delta Lake, and Notebooks.
- Knowledge of AWS, Azure, or GCP cloud data platforms and experience with Docker and Kubernetes.
- Experience with ETL/ELT, data lakes, Kafka, and Spark Streaming.
- Familiarity with MLOps toolchains including Airflow and Feature Store technologies.
- Experience solving large-scale data problems; published research or open-source contributions are a plus.
- Strong communication, collaboration, and mentoring skills.
Benefits
- Health, life, and disability insurance.
- Retirement savings plans and a discounted employee stock purchase program.
- Paid time off for holidays, family leave, and company-wide wellness days.
- Flexible work accommodations supporting work/life harmony.
- Career progression planning with dedicated monthly time for learning and development.
- Business Resource Groups, volunteerism, sustainability initiatives, and a collaborative global community.
Tech Stack
Apache AirflowApache KafkaApache SparkAWSAzureDatabricksDockerFastAPIFlaskGoogle Cloud PlatformHugging Face TransformersKubernetesMLflowNumPyPandasPythonPyTorchSQLTensorFlow
Categories
About FactSet
FactSet builds a financial data and analytics platform used by asset managers, investment banks, hedge funds, and wealth managers for research, portfolio management, trading, and risk. Its products include the FactSet workstation, data feeds and APIs, and workflow tools like OMS/EMS, sold primarily via subscription licensing. Founded in 1978 and headquartered in Norwalk, Connecticut, FactSet is a public company listed on the NYSE (ticker: FDS).