Lead Data Scientist - UK 12 Month FTC

We are tech transformation specialists, uniting human expertise with AI to create scalable tech solutions. With over 6,500 CI&Ters around the world, we’ve built partnerships with more than 1,000 clients during our 30 years of history. Artificial Intelligence is our reality.

General Description: We are looking for scientists who are passionate about data and are eager to tackle big challenges using Data Science and Machine Learning. The main focus of this role is to solve non-trivial business problems in Fortune 500 companies. This person will mostly work with a mix of structured and unstructured data, using scientific methods and state-of-the-art techniques and tools to help our customers achieve their business objectives.

Responsibilities:

• Understand complex business problems and translate them into structured data problems.
• Capture and explore complex data sets (structured and unstructured data).
• Prototype models of different complexity (business analysis, statistical models, machine learning) using modern data science tools (Notebooks, Clouds).
• Design and implement machine learning models, metrics, and application of feature engineering techniques applied to customer problems.
• Support pre-sales in business opportunities and engineering teams in the implementation of production-ready solutions involving machine learning.
• Evaluate hypotheses and the impact of machine learning algorithms on key business metrics.
• Simulations and offline/online experimentation (via A/B tests) is part of the game.
• Research and understand user behavior patterns, such as user engagement and segmentation, using machine learning models to help test hypotheses.
• Communicate findings effectively to an audience of engineers and executives.

Required Qualifications:

• Bachelor’s Degree in Computer Science/Engineering, Applied Math, Statistics, Physics or other related quantitative areas.
• Advanced oral and written communication skills in English.
• Ability to understand mathematical models and algorithms in research papers and implement them into running software for Proof-of-Concepts and projects.
• Ability to explore big data without a specific problem defined, in order to come up with the right questions and provide interesting findings.
• Ability to provide visibility of the progress of tasks to the team by means of small deliverables.
• Proficient in computer languages like Python or R, and SQL, making use of the best frameworks for machine learning pipelines, data visualization, manipulation, transforming, models training and evaluation, and models deployment.
• Experience with common feature engineering techniques and machine learning algorithms for Supervised and Unsupervised Learning, like Regression, Classification, Clustering, Dimensionality Reduction, Association Rules, Ranking, and Recommender Systems.
• Experience with Natural Language Processing (NLP and NLU).
• Experience using Generative AI systems (e.g. ChatGPT) and best practices (e.g. Prompt Engineering).
• Understanding the key concepts on how to apply Generative AI in building RAG solutions (embeddings, dense search).
• Business sense and consulting behavior to identify and breakdown problems, define and evaluate hypotheses.
• Think critically and act in a detail-oriented fashion while keeping the 'big picture' in mind.
• Ability to provide creative and innovative approaches to problem solving.
• Ability to work independently and within a collaborative team environment.

Desired Qualifications:

• Masters or PhD in Machine Learning / Data Mining / Statistics.
• Experience in building advanced Information Retrieval or Question Answering systems using NLP and Generative AI techniques (e.g. RAG and GraphRAG).
• Experience with construction and integration of Knowledge Graphs.

Collaboration is our superpower, diversity unites us, and excellence is our standard. We value diverse identities and life experiences, fostering a diverse, inclusive, and safe work environment. We encourage applications from diverse and underrepresented groups to our job positions.