Data Scientist (VOLWH)

Locally Compact, Inc. has the following position available in New York, NY: Data Scientist (VOL-WH): Optimize quantitative forecasting models to predict multi-cycle equity returns and improve trading performance. Incorporate risk constraints and portfolio optimization enhancements into live trading systems to improve risk-adjusted returns. Design and implement systems to ensure data correctness and monitor data health in data stores and live feeds. Perform extemporaneous analyses on research and production trading systems with leadership. Harness financial expertise and statistical analysis to gain actionable insights into production trading and research systems. Conduct rigorous statistical research to enhance model performance, including feature selection, signal evaluation, and back-testing of predictive strategies. Maintain automated research pipelines for feature generation, model training, validation, and performance monitoring. Analyze production trading systems to identify performance drivers, risk exposures, and abnormal behaviors; communicate findings and recommendations clearly to leadership and stakeholders. Perform ad hoc quantitative analyses on research and production environments to diagnose issues, evaluate new signals, and inform strategic decision-making. Build systems to ensure data integrity, correctness, and health across researchdatasets and live market feeds.Minimum Requirements: Masters degree or equivalent in Statistics, Data Science, Operations Research, Computer Science, or a closely related field and six (6) months related experience. Special Requirements: Must have each of the following: 1. Six months of demonstrated applied industry experience (including internships) working end-to-end with complex datasets, including data curation, querying, aggregation, exploratory analysis, modeling, and visualization. 2. Demonstrated experience applying statistical and quantitative methods to analyze data, identify patterns, perform root cause analysis, and generate actionable insights. 3. Demonstrated experience formulating business or research problems mathematically and deriving structured, data-driven solutions. 4. Demonstrated experience working with Python for data analysis and modeling, including Pandas and NumPy. 5. Demonstrated experience working with R and SQL to query large-scale datasets. 6. Demonstrated experience with statistical modeling techniques such as regression, time-series analysis (e.g., auto-regression, auto-correlation), hypothesis testing, or dimensionality reduction (e.g., PCA). 7. Demonstrated experience with software development, including experience with Linux/Unix, bash, and git. 8. Demonstrated experience refining ambiguous requests into well-defined analyses and delivering clear, concise reports demonstrating strong communication skills and teamwork abilities. 9. Demonstrated experience developing code in a production environment, including familiarity with CI/CD workflows and workflow orchestration tools (e.g., Airflow). 10. Demonstrated experience working in fast-paced, collaborative, or geographically distributed environments. Employer will accept experience gained concurrently. Submit resume to: [email protected]. Must reference job title and job code. Annual salary range: $160,000.00 - $180,000.00 per year.