Senior Data Scientist

Kpler; London; On-site; GBP 70,000 - 100,000; Full time

Job summary

A leading company in global trade information is seeking a senior data scientist to enhance their understanding of commodity flows using data-driven models. This role involves creating innovative algorithms and deploying machine learning solutions in a collaborative environment. The ideal candidate will have a strong background in Python and cloud technologies, ideally AWS, along with a passion for tackling complex challenges in the commodity market.

Qualifications

• At least 5 years of experience in data science with production deployment.
• Proven experience in delivering end-to-end ML solutions.
• Expertise in cloud platforms, preferably AWS.

Responsibilities

• Develop algorithms for commodities flow understanding and anomaly detection.
• Drive design and deployment of data science models.
• Mentor junior data scientists and lead projects.

Skills

Python

Data Science

Machine Learning

Big Data

Geospatial Data

Anomaly Detection

Education

Ph.D. in a quantitative field

Tools

TensorFlow

PyTorch

AWS

Spark

Kafka

Job description

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At Kpler, we simplify global trade information and provide valuable insights. Founded in 2014, our goal is to help over 10,000 organizations by offering the best intelligence on commodities, energy, and maritime through a single platform. Working at Kpler means you'll be a key player in turning complex data into strategic resources for our clients. Your role involves creating data-driven stories that empower clients in their industries. Your expertise helps Kpler navigate markets successfully. Your journey starts here, where innovation meets impact. Join our team of 500+ talented people from 35+ countries worldwide.

Purpose of the role

Maritime domain awareness and commodity tracking involve the effective fusion of fragmented information that composes the complex commodity flows landscape. When combined efficiently, vessel tracking data and trading history, commodity supply and demand, proprietary trading data, and machine learning algorithms provide an understanding of events at ports and on open seas at different levels of granularity. Rapidly evolving global geopolitical developments and tensions significantly affect trading, disrupting the supply chain and altering commodity flow patterns, which brings more uncertainty about the modeling of these phenomena. As a senior data scientist with Kpler’s Flows team, you will develop algorithms that extend our understanding of commodities flows in space and time by devising forecasting models, predicting future trades, and detecting anomalies in data and behavior of various players.

Some of the exciting projects you will work on include:

1. Driving the design, rapid experimentation, development, testing, and deployment of data science models for flow forecasting and anomaly detection;
2. Optimizing and fine-tuning models in production, overseeing continuous monitoring, and handling model and data drift promptly;
3. Building robust pipelines for integrating diverse data sources, including big geospatial data, ship mobility data, and document recognition; researching methods, data sources, and features to improve model accuracy in a changing global environment;

As a senior data scientist, you will:

• Devise efficient solutions for ML/Big Data challenges using current methods and technologies;
• Work across the stack to deliver features end-to-end, from prototyping to deployment and maintenance;
• Ensure scalable, cost-effective design decisions that enhance performance;
• Own parts of our service, leading projects independently, impacting the company, and growing professionally;
• Identify new project opportunities and collaborate with product teams to develop value-adding features;
• Share knowledge, document insights, and communicate complex concepts effectively to diverse audiences;
• Mentor junior data scientists and act as Tech Lead on projects;
• Participate in Kpler’s Machine Learning community, tackling a broad range of ML problems.

Our Machine Learning tech stack includes:

• Python, ML libraries (TensorFlow, PyTorch, scikit-learn, transformers, XGBoost, ResNet), geospatial libraries (shapely, geopandas, rasterio), CV libraries (scikit-image, OpenCV, YOLO, Detectron2)
• AWS, Postgres, Apache Airflow, Kafka, Spark

Mandatory requirements:

• At least 5 years of experience in data science, with deployment into production;
• Proven experience delivering end-to-end ML solutions that create business value;
• Proficiency in Python;
• Expertise with at least one cloud platform, preferably AWS;
• Fluency in English.

Nice to haves (not mandatory):

• Expertise in geospatial data and mobility analytics;
• Experience with big data technologies like Spark and Kafka;
• Experience with ML pipeline tools (MLflow, Sagemaker) or building pipelines with Docker, Kubernetes, Airflow;
• Ph.D. in a quantitative field;
• Knowledge of the shipping industry and commodity trading;
• Familiarity with software engineering best practices;
• Commitment to code simplicity, performance, and detail;
• Experience in an international environment.

We are a dynamic company dedicated to fostering connections and innovating solutions to market challenges. If you are driven by customer satisfaction and turning ideas into reality, join us on this exciting journey. We value diversity and are committed to an inclusive, fair work environment, welcoming applicants from all backgrounds.