Data Scientist, Energy & Industrials

BAM's Data Science & AI (DSAI) group consists of data scientists, engineers, and researchers who support the firm's research initiatives across fundamental and quantitative strategies. The team i

BAM's Data Science & AI (DSAI) group consists of data scientists, engineers, and researchers who support the firm's research initiatives across fundamental and quantitative strategies.

• edge data platforms to analyze datasets and generate investment signals.

DSAI works with each investment strategy at BAM, providing analytical rigor and data-driven insights for investment decisions.

You'll have the opportunity to partner with senior investors, to lead research design on investment themes, and develop advanced models for alpha generation.

• Partner with Portfolio Managers: Identify and frame key investment debates in the Commodities & Energy space, and design and conduct data-driven research to address them.
• Forecast the Future: Use advances techniques (LLMs, graph analytics, machine learning, Bayesian frameworks) to create predictions which have high accuracy and low latency.
• Leverage AI: Use the latest in LLMs and BAM's AI infrastructure to extract insights and deliver Agentic solutions for our Portfolio Management teams.
• Build & Scale Data Products: Lead the development of data products and scale solutions that empower investment teams and drive alpha generation.
• Shape Sector Strategy: Contribute to the development and execution of sector-level data strategies, driving engagement and adoption of the team's products.
• Innovate with Investment Staff: Brainstorm creative applications of data in the investment process, pushing the boundaries of what's possible.

• Alpha-First Mindset: A passion for delivering value to investment teams by questioning the consensus and looking for informational advantages in data.
• Continuous Pursuit of Excellence : The ability to deliver results and an internal drive to constantly iterate and improve.
• Technical Mastery: Solid command of statistics, analytics, and machine learning, with a proven track record of informing investment or business decisions.
• Machine Learning Skills: Demonstrated ability to apply advanced quantitative techniques to data including a broad spectrum of machine learning methodologies.
• Applied AI: experience or familiarity with LLMs and prompt engineering.
• Sector Expertise & Curiosity: Deep knowledge and intellectual curiosity in Energy, Commodities or Industrials; experience in key domains including geospatial, maritime, weather, remote sensing, transport and logistics, data panelization, exploratory data analysis (EDA) among others.
• Proven Experience: 4+ years in data science, data analytics, or a related field.
• Educational Background: BS or MS in Mathematics, Finance/Economics, Computer Science, Information Management, Statistics, Engineering, or Technology.
• Crisp Presentation & Communication: Ability to distill complex technical concepts to non-technical audiences.

• Coding: Python and SQL
• Tech Stack Familiarity: Experience with any of the following is a plus: data analytics (Databricks/Spark, Snowflake, Jupyter), visualization tools (matplotlib, plotly, Tableau), web application frameworks (Dash, streamlit), cloud infrastructure (AWS/GCP/Azure, Apache Airflow, Jenkins, Docker), and Excel.

If you're passionate about leveraging data to solve complex problems and drive investment performance, we want to meet you.