Statistical Data Scientist...

Job Description

COMPANY OVERVIEW:

Energy is always evolving. At Hartree Partners, we use our decades of experience in

the physical and financial energy and commodities markets to explore the opportunities this evolution provides. We assist our customers in participating in new markets and navigating their complexities for maximum revenues at minimum risk.

We provide a wide range of services to a substantial and diversified customer base that includes corporations, financial institutions, governments and individuals. Founded in 1997, the firm is headquartered in New York and maintains offices in many financial centers around the world. Hartree Partners LP is owned by the company’s Managing Partners, senior staff, and Oaktree Capital.

Find out more about us by visiting our website at:http://www.hartreepartners.com/

ROLE OVERVIEW:

Hartree Partners is growing its data-driven analytics team and is hiring a Statistical Data Scientist to sharpen our view of weather-driven risk and support wider supply-and-demand modelling for power & gas trading. You will play a pivotal role in shaping our data strategy and driving the development of our modelling approaches. You will collaborate with cross-functional teams to design, implement, and optimize data pipelines and predictive models that inform trading decisions and enhance operational efficiency.

RESPONSIBILITIES:

Primary Focus:

• Probabilistic Weather Modelling: Research and prototype probabilistic methods (Bayesian inference, state-space filtering, change-detection tests, etc.) that flag when fresh weather guidance materially diverges from prior outlooks.
  
• Continuous Development and Improvement: Calibrate confidence metrics with historical data and measure their value to trading & risk learning models. Continuously improve these models based on real-time data and feedback from trading activities.
  
• Model Communication: Explain uncertainty clearly, turning numbers into concise narratives and action-oriented alerts
  
  Broader Contributions:
  
  
• Build and refine statistical / ML models for short- to medium-term demand, renewables output, and other fundamental time series.
  
• Help design feature pipelines, scenario tools and model-performance dashboards used daily by traders and analysts.
  
• Pitch in on ad-hoc analytics projects—anything from volatility clustering studies to optimisation of storage dispatch—whenever the desk needs statistical horsepower.
  
  REQUIREMENTS:
  
  
• Minimum of a degree in Statistics, Applied Maths, Physics or related field.
  
• Minimum of 2 years working in a Data Science related role
  
• Proven depth in probability & inference (e.g., Bayesian updating, time-series/state-space models, extreme-value theory).
  
• Hands-on Python for numerical analysis (numpy, pandas, xarray, SciPy/PyMC/PyTorch, or similar).
  
• Experience validating models with historical data and communicating results to non-specialists.
  
• Exposure to real-time data engineering (Kafka, Airflow, dbt)
  
• Track record turning research code into production services (CI/CD, containers etc)
  
• Strong SQL and data-management skills; experience querying large analytical databases (Snowflake highly desirable, but Redshift/BigQuery/ClickHouse etc. also welcome).
  
  PREFERRED QUALIFICATIONS:
  
  
• Meteorological understanding / experience with weather modelling
  
• Prior knowledge or experience in the power markets or energy sector.
  
• Experience with cloud platforms (e.g., AWS, GCP, Azure) and MLOps practices.
  
• Familiarity with data visualization tools (e.g., Tableau, Power BI).
  
  COMPENSATION & BENEFITS:
  
  
• Competitive salary + bonus.
  
• Comprehensive benefits package including health insurance, pension plan.
  
• Hybrid working arrangement (minimum 3 days in the London office)