21 hours 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 data-processing workflows using Databricks, Spark, Delta Lake, Feature Stores, and MLOps practices.
- Develop and fine-tune LLMs and generative AI applications using prompt engineering and retrieval-augmented generation.
- Address data challenges including entity disambiguation, real-time risk analytics, NLP, graph data modeling, and anomaly detection.
- Collaborate with engineers, product managers, and UX teams to deliver high-performance solutions.
- Translate current research and new machine learning techniques into production systems.
- Mentor junior data scientists and engineers on machine learning, GenAI, and engineering best practices.
Requirements
- Bachelor’s or master’s degree in Computer Science, Engineering, 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 Transformers, including practical GenAI development.
- Experience training or fine-tuning LLMs and working with OpenAI, HuggingFace, or Google Gemini.
- Hands-on experience with Databricks Workspace, MLflow, Delta Lake, and Notebooks.
- Knowledge of AWS, Azure, GCP, Docker, Kubernetes, ETL/ELT, data lakes, Kafka, and Spark Streaming.
- Familiarity with Airflow, Feature Store, and modern MLOps toolchains.
- 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 learning and development time.
- Business Resource Groups and opportunities for volunteerism and sustainability.
- Opportunity to join an S&P 500 company with a global community and entrepreneurial culture.
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).