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Company Overview
This specialized AI and machine learning division of a global management consulting firm helps organizations across various industries leverage the power of data and AI to drive strategic decisions, improve performance, and foster innovation.
Data Scientist
As a Data Scientist, the individual will:
Partner with their clients, from data owners and users to C-level executives, to understand their needs and build impactful analytics solutions
Contribute to cross-functional problem-solving sessions with their team and deliver presentations to colleagues and clients
Translate business problems into analytical problems and develop models aimed at solving their clients’ and users’ problems and ensure they are evaluated with the relevant metrics
Write highly optimized code to advance their internal Data Science Toolbox
Add real-world impact to academic expertise, as they will be encouraged to write papers and present at meetings and conferences should they wish
Take part in R&D projects; attend conferences such as NIPS and ICML as well as data science retrospectives where they will have the opportunity to share and learn from their co-workers
Work in one of the most advanced data science teams globally
Work on the frameworks and libraries that their teams of data scientists and data engineers use to progress from data to impact
Guide global companies through data science solutions to transform their businesses and enhance performance across industries including healthcare, automotive, energy and elite sport
The qualifications and skills sought are:
Bachelor’s, master’s or PhD level in a discipline such as: computer science, machine learning, applied statistics, mathematics, engineering or artificial intelligence
2+ years of professional experience in applying machine learning and data mining techniques to real problems with copious amounts of data
Programming experience (focus on machine learning): SQL and Python’s Data Science stack are a must; good knowledge of at least one big data framework (Pyspark, Hive, Hadoop) is a plus; R, SPSS, SAS (nice to have); Software Engineering is a plus
Ability to prototype statistical analysis and modeling algorithms and apply these algorithms for data-driven solutions to problems in new domains
Experience deploying technology applied to business problems is a plus
Knowledge in applying machine learning solution to real problems with complex and/or big amounts of data
Knowledge in prompt engineering & GenAI application building (RAG, Agentic systems). Having basic understanding of Engineering standards, QA/Risk Management
Willingness to travel
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