National AI Awards 2025Discover AI's trailblazers! Join us to celebrate innovation and nominate industry leaders.

Nominate & Attend

Statistical Data Scientist

Hartree Partners
London
4 weeks ago
Applications closed

Related Jobs

View all jobs

62969 – Data Scientist

Principal Data Scientist

Principal Data Scientist

Principal Data Scientist

Data Scientist, Ad Fraud Detection, Traffic Quality ML

Data Scientist, Digital Acceleration

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)
National AI Awards 2025

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

How to Find Hidden Machine Learning Jobs in the UK Using Professional Bodies like BCS, Turing Society & More

Machine learning (ML) continues to transform sectors across the UK—from fintech and retail to healthtech and autonomous systems. But while the demand for ML engineers, researchers, and applied scientists is growing, many of the best opportunities are never posted on traditional job boards. So, where do you find them? The answer lies in professional bodies, academic-industry networks, and tight-knit ML communities. In this guide, we’ll show you how to uncover hidden machine learning jobs in the UK by engaging with groups like the BCS (The Chartered Institute for IT), Turing Society, Alan Turing Institute, and others. We’ll explore how to use member directories, CPD events, SIGs (Special Interest Groups), and community projects to build connections, gain early access to job leads, and raise your professional profile in the ML ecosystem.

How to Get a Better Machine Learning Job After a Lay-Off or Redundancy

Redundancy in machine learning can feel especially frustrating when your role was technically advanced, strategically important, or AI-facing. But the UK still has strong demand for machine learning professionals across fintech, healthtech, retail, cybersecurity, autonomous systems, and generative AI. Whether you're a research-oriented ML engineer, production-focused MLOps developer, or applied scientist, this guide is designed to help you bounce back from redundancy and find a better opportunity that suits your goals.

Machine Learning Jobs Salary Calculator 2025: Figure Out Your True Worth in Seconds

Why last year’s pay survey is useless for UK ML professionals today Ask a Machine Learning Engineer wrangling transformer checkpoints, an MLOps Lead firefighting drift alarms, or a Research Scientist training diffusion models at 3 a.m.: “Am I earning what I deserve?” The honest answer changes monthly. A single OpenAI model drop doubles GPU demand, healthcare regulators release fresh explainability guidance, & a fintech unicorn pays six figures for vector‑search expertise. Each shock nudges salary bands. Any PDF salary guide printed in 2024 now looks like an outdated Jupyter notebook—missing the gen‑AI tsunami, the surge in edge inference, & the UK’s new Responsible‑AI framework. To give ML professionals an accurate benchmark, MachineLearningJobs.co.uk distilled a transparent, three‑factor formula that estimates a realistic 2025 salary in under a minute. Feed in your discipline, UK region, & seniority; you’ll receive a defensible figure—no stale averages, no guesswork. This article unpacks the formula, highlights the forces driving ML pay skyward, & offers five practical moves to boost your value inside the next ninety days.