at Balyasny Asset Management, L.P. in Chicago, Illinois, United States
Job Description
Design, develop, and deploy processes to connect to various data sources, including web, vendor data, internal database, and flat files in multiple formats, such as structured/unstructured, near real-time, and market/industry-related. Deploy automated data collection to create scalable data structures and data assets, including connecting and ingesting data, identifying issues and abnormalities, and cleaning data and delivering to data warehouses and end users. Utilize modern data architecture and frameworks, including Airflow, Kubernetes, AWS, Snowflake, Jupyter, and Papermill. Become a data owner for specific industry datasets, including understanding the data life cycle (releases and updates), mitigating risks associated with data used in products (outliers, coverage, and completeness), and understanding business use cases (analytics and KPIs derived from the data). Specialize in industry subsectors to be apprised of the latest investment debates and understand how data could support answering each question, including knowing which debates exist, how they impact the sector and subsector, who is leading and lagging in the debate, which datasets might contribute meaningfully to quantitatively answer the question, and how data could be transformed and presented to answer specific industry questions. Collaborate with data strategy by staying aware of new industry datasets from vendors and open-sources. Evaluate datasets, measuring the total impact to the investment process, determining criteria to evaluate return on data investments, and communicating findings and recommendations to both central data teams and individual investment teams. Present data, including conceiving and creating compelling visualizations that can answer questions and tell a data story. Create custom charts and dashboards through code (Python) and visualization tools (Excel and Tableau). Create full visualization pipelines and automate delivery of updated charts and insights. Analyze data using standard and advanced statistical tools, including supplementing open-source packages with scalable algorithms that can be productionized and reused by colleagues. Utilize machine learning techniques, including fitting models, assessing feature importance and determining optimal feature matrices, evaluating test statistics, and selecting appropriate error measurements and interpreting their values. Work with investment teams, including analysts and portfolio managers, and actively collaborate with investment staff to brainstorm creative uses for data in the investment process. Identify and share data themes and effectively communicate their importance to investment staff. Teach investment staff how to incorporate and leverage data tools and data insights into their current workflow. Work with portfolio managers to prioritize data and analytics projects that show strong potential in answering questions on their portfolio, coverage, and industry. Work with data stewardship and architecture; Python automation; investment management in the energy sector; predictive modeling; stochastic processes; statistical model maintenance; and, machine learning.
Job Requirements: Bachelor’s degree in Statistics, Mathematics, Data Science, or a related field of study, plus two (2) years of experience with data stewardship and architecture; Python automation; investment management in the energy sector; predictive modeling; stochastic processes; statistical model maintenance; and, machine learning.
Email resume to HRRecruiting@bamfunds.com or mail resume to Hannah Ogren, Balyasny Asset Management, LP, 444 West Lake Street, 50th Floor, Chicago, IL 60606. Must Ref# AL23BAMIL. No phone calls.
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