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Kpler

Data Scientist

London
Posted about 15 hours ago
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About Kpler

At Kpler, we are dedicated to helping our clients navigate complex markets with ease. By simplifying global trade information and providing valuable insights, we empower organisations to make informed decisions in commodities, energy, and maritime sectors.

Since our founding in 2014, we have focused on delivering top-tier intelligence through user-friendly platforms. Our team of over 850 experts from 69 countries works tirelessly to transform intricate data into actionable strategies, ensuring our clients stay ahead in a dynamic market landscape.

Join us to leverage cutting-edge innovation for impactful results and experience unparalleled support on your journey to success.

Data Scientist

The Commodities tribe at Kpler runs production ML models that predict what cargo a vessel is carrying (Product Estimation) and where in-transit vessels are headed (Destination Forecast), and where they are expected to arrive (ETA)— across LNG, DRY, LPG, and LIQUIDS. These predictions feed directly into Kpler's cargo intelligence platform, consumed by market analysts, trading desks, and external customers worldwide.

You will own the science behind these models: designing and evaluating features from maritime AIS data, H3 geospatial routing distributions, transit statistics, and commodity-specific signals; running structured experiments on ML Flow based platform; and pushing the accuracy, coverage, and reliability of predictions forward.

You are not handed a Jupyter notebook and a dataset. You work in a production system with real-time inference running every 1–3 hours across 4 commodity types, and your model changes need to be validated against a running parallel baseline before they go live. The new platform is being built specifically to make the experiment loop fast enough that this level of rigour does not slow you down.

Reasons to use Rodeo

I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?

Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.

Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.

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Graduate Consultant — 2026 Scheme

PwC·London, UK
£35,000/yr

Why you're a good match

Strong

Your economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.

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Why you're a good match

You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.

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Strong

Experience fit

Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.

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Only hits

No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.

Key Responsibilities

  • Own the feature engineering roadmap for ETA & Destination Forecast across all 4 commodity types — propose and implement new features as dbt models using Airflow to orchestrate the data pipelines, and validate their impact through structured experiments.
  • Design and run experiments using kpler-ml framework, logging all runs from train to evaluation to MLflow and producing structured comparison reports against the production baseline before any promotion.
  • Work directly with Commodities Market Analysts and product stakeholders to understand where prediction quality matters most commercially — and use that to prioritise the experiment backlog.
  • Contribute to the drift monitoring setup — validate PSI/KS thresholds using MLFlow against historical inference batches; define what constitutes a meaningful drift signal for PE and DF specifically.
  • Document experiment decisions in MLflow and Confluence documents — the experiment history is a first-class artifact, not an afterthought.

Experience & Background

  • 2+ years applying ML to real-world production problems — not research or hackathon work, but models running in production with real consequences for errors
  • Experience with geospatial or sequential data — vessel trajectories, routing patterns, H3/S2 grid systems, or equivalent spatial representations
  • Python proficiency at a level sufficient to implement new features, write dbt models, and script experiments — not just use notebooks
  • Familiarity with MLflow or equivalent experiment tracking (Weights & Biases, Neptune, etc.)

Desirable:

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  • Domain knowledge of maritime shipping, commodity trading, or cargo intelligence — understanding what a port call sequence or a vessel's draught profile means physically, not just statistically
  • Familiarity with Redshift or columnar warehouses for large-scale feature queries and dbt (authoring or reading SQL models)

Our Company

We are a dynamic company dedicated to nurturing connections and innovating solutions to tackle market challenges head-on. If you thrive on customer satisfaction and turning ideas into reality, then you’ve found your ideal destination.

  • We make things happen
  • We act decisively and with purpose, going the extra mile.
  • We build together
  • We foster relationships and develop creative solutions to address market challenges.
  • We are here to help
  • We are accessible and supportive to colleagues and clients with a friendly approach.

Our People Pledge

Don’t meet every single requirement? Research shows that women and people of color are less likely than others to apply if they feel like they don’t match 100% of the job requirements. Don’t let the confidence gap stand in your way, we’d love to hear from you! We understand that experience comes in many different forms and are dedicated to adding new perspectives to the team.

Kpler is committed to providing a fair, inclusive and diverse work-environment. We believe that different perspectives lead to better ideas, and better ideas allow us to better understand the needs and interests of our diverse, global community. We welcome people of different backgrounds, experiences, abilities and perspectives and are an equal opportunity employer.

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Skills

Machine Learning
Python
Feature Engineering
Geospatial Data Analysis
MLflow
dbt
Airflow
SQL
Redshift
Sequential Data Analysis
Experiment Design
Drift Monitoring

Location

London, England, United Kingdom

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