LSG Digital Finance Analytics team is seeking to analyze large datasets, automate processes, and communicate insights to senior management to support financial planning, analysis, and forecasting.
Requirements
- Proficiency in Python (Pandas, NumPy, Scikit-learn, TensorFlow/PyTorch), SQL, and AI/ML lifecycle platforms.
- Strong understanding of data governance and data quality.
- Experience with data platforms like PowerBI, Azure Databricks, and Fabric.
- Experience with AI infrastructure.
- Experience with Kubeflow, AWS SageMaker, or Azure ML.
Responsibilities
- Design and validate Machine Learning, Deep Learning, and Natural Language Processing (NLP) models for portfolio optimization, risk analytics, performance attribution, and capital allocation.
- Build scalable data pipelines using Python, SQL (MySQL), and R. Perform feature engineering, data normalization, and generate reports and financial data.
- Collaborate with engineering teams to deploy models using Kubeflow, AWS SageMaker, or Azure ML. Ensure robust model governance, version control, and production readiness.
- Conduct factor analysis, scenario modeling, and backtesting to evaluate model performance.
- Partner with Data Science, Investment Research, and Portfolio Strategy teams to align AI solutions with client mandates, investment policy statements, and risk-adjusted return objectives.
Other
- Bachelor’s or Master’s degree in Computer Science, Machine Learning, Mathematics, Statistics, Econometrics, or related quantitative fields.
- Excellent interpersonal skills to present complex technical concepts to executive stakeholders.
- At least 120 hours paid time off (PTO), 10 paid holidays annually, paid parental leave (3 weeks for bonding and 8 weeks for caregiver leave)
- Retirement and savings programs, such as our competitive 401(k) U.S. retirement savings plan
- Employees’ Stock Purchase Plan (ESPP) offers eligible colleagues the opportunity to purchase company stock at a discount
