Lead Data Scientist - UK 12 Month FTC

CI&T Software S.A.
London
1 month ago
Applications closed

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Lead Data Scientist

Lead Data Scientist

Lead Data Scientist

Lead Data Scientist

Lead Data Scientist

Lead Data Scientist (London Area)

We are tech transformation specialists, uniting humanexpertise with AI to create scalable tech solutions. With over6,500 CI&Ters around the world, we’ve built partnerships withmore than 1,000 clients during our 30 years of history. ArtificialIntelligence is our reality. When applying for one of ourpositions, you’re agreeing to the use of AI in the early phases ofthe selection process, where your profile will be evaluated by ourvirtual assistant. For more information, access our opportunities’page. General Description: We are looking for scientists who arepassionate about data and are eager to tackle big challenges usingData Science and Machine Learning. The main focus of this role isto solve non-trivial business problems in Fortune 500 companies.This person will mostly work with a mix of structured andunstructured data, using scientific methods and state-of-the-arttechniques and tools to help our customers achieve their businessobjectives. Responsibilities: 1. Understand complex businessproblems and translate them into structured data problems. 2.Capture and explore complex data sets (structured and unstructureddata). 3. Prototype models of different complexity (businessanalysis, statistical models, machine learning) using modern datascience tools (Notebooks, Clouds). 4. Design and implement machinelearning models, metrics, and apply feature engineering techniquesto customer problems. 5. Support pre-sales in businessopportunities and the engineering teams in the implementation ofproduction-ready solutions involving machine learning. 6. Evaluatehypotheses and the impact of machine learning algorithms on keybusiness metrics. Simulations and offline/online experimentation(via A/B tests) is part of the game. 7. Research and understanduser behavior patterns, such as user engagement and segmentation,using machine learning models to help test hypotheses. 8.Communicate findings effectively to an audience of engineers andexecutives. Required Qualifications: 1. Bachelor’s Degree inComputer Science/Engineering, Applied Math, Statistics, Physics, orother related quantitative areas. 2. Advanced oral and writtencommunication skills in English. 3. Ability to understandmathematical models and algorithms in research papers, and toimplement them into running software for Proof-of-Concepts andprojects. 4. Ability to explore big data without a specific problemdefined, in order to come up with the right questions and provideinteresting findings. 5. Ability to provide visibility of theprogress of tasks to the team by means of small deliverables. 6.Proficient in computer languages like Python or R, and SQL, makinguse of the best frameworks for machine learning pipelines, datavisualization, manipulation, model training and evaluation, andmodel deployment. 7. Experience with common feature engineeringtechniques and machine learning algorithms for Supervised andUnsupervised Learning, like Regression, Classification, Clustering,Dimensionality Reduction, Association Rules, Ranking, andRecommender Systems. 8. Experience with Natural Language Processing(NLP and NLU). 9. Experience using Generative AI systems (e.g.,ChatGPT) and best practices (e.g., Prompt Engineering). 10.Understanding the key concepts on how to apply Generative AI inbuilding RAG solutions (embeddings, dense search). 11. Businesssense and consulting behavior to identify and breakdown problems,define and evaluate hypotheses. 12. Think critically and act in adetail-oriented fashion while keeping the "big picture" in mind.13. Ability to provide creative and innovative approaches toproblem solving. 14. Ability to work independently and within acollaborative team environment. Desired Qualifications: 1. Mastersor PhD in Machine Learning / Data Mining / Statistics. 2.Experience in building advanced Information Retrieval or QuestionAnswering systems using NLP and Generative AI techniques (e.g., RAGand GraphRAG). 3. Experience with construction and integration ofKnowledge Graphs. Collaboration is our superpower, diversity unitesus, and excellence is our standard. We value diverse identities andlife experiences, fostering a diverse, inclusive, and safe workenvironment. We encourage applications from diverse andunderrepresented groups to our job positions.#J-18808-Ljbffr

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