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SummitTX Capital is seeking a Research Engineer to build and scale their systematic data platform, which is crucial for alpha research and production signals. This platform will support various investment strategies and requires end-to-end development from data acquisition to model deployment and monitoring.

Requirements

• Strong Python and SQL fundamentals; comfort with Git and testing frameworks
• Hands-on experience with DBT, DuckDB or Spark, and modern data-quality toolkits
• Familiarity with Databricks (Lakehouse, Unity Catalog) and AWS data services (S3, Glue/Athena, Lake Formation)
• Exposure to ML frameworks (pandas, scikit-learn, PyTorch, MLflow) and feature pipelines
• Experience with visualization and BI tools (e.g., Plotly, Tableau/Power BI), and Financial Data Platform (e.g. Bloomberg Terminal)
• Experience in GenAI/LLM applications (prompt engineering, RAG, agentic workflow)
• Coursework or internship experience in data modeling, ETL/ELT, ML/statistics, or time-series analysis

Responsibilities

• Design, build, and maintain systematic data pipelines, including ingestion, medallion-style data modeling, feature engineering, and experiment tracking
• Operationalize robust ELT workflows using DBT/SQL and Python on Databricks, with strong enforcement of data quality, lineage, and documentation
• Develop research-grade datasets and features across market, alternative, and fundamental domains to support L/S Equity and systematic strategies
• Productionize models and alpha signals with CI/CD pipelines, model registries, monitoring, and cost/performance optimization on Databricks and AWS
• Partner with PMs and Analysts to translate investment hypotheses into testable research artifacts, delivering clear results, visualizations, and readouts to guide decision-making
• Contribute to the evolution of the data platform roadmap, including observability, governance, access controls, cataloging, and documentation standards
• Implement experiment tracking, model registry, and monitoring frameworks to ensure transparency, reproducibility, and performance measurement of models and signals

Other

• Partner daily with portfolio managers, analysts, the central research team, risk, and operations.
• Partner with PMs and Analysts to translate investment hypotheses into testable research artifacts, delivering clear results, visualizations, and readouts to guide decision-making.
• Clear communication skills and ability to partner with investment, risk, and operations stakeholders.
• Provide ongoing research readouts, visualizations, and clear communication to investment teams, helping guide decision-making and accelerate alpha discovery.
• BS or MS in Data Science, Statistics, Data Engineering, Applied Math, Computer Science, or related field with strong academic performance