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Eviden is an Atos Group business with an annual revenue of circa € 5 billion and a global leader in data-driven, trusted and sustainable digital transformation. As a next generation digital business with worldwide leading positions in digital, cloud, data, advanced computing and security, it brings deep expertise for all industries in more than 47 countries. By uniting unique high-end technologies across the full digital continuum with 55,000 world-class talents, Eviden expands the possibilities of data and technology, now and for generations to come. About the practice: The
DAA practice
represents a growing capability within Eviden and comprises a talented team of analysts, developers, consultants and architects covering all aspects of the information management lifecycle, from data management through to business intelligence and analytics. Eviden works with a range of large organisations facing an ever-increasing demand to realise greater value from their data, understand their business challenges, and are seeking the skills to develop advanced analytics, statistical modelling, and AI/ML routines. About the role: We are seeking a Data Scientist to undertake independent work, to play a role in the mentoring and development of the wider team, and to deliver data science projects, either individually or as part of a team. You will build machine learning pipelines for clients, frequently as part of a broader project involving scoping, gathering requirements, planning and interpretation of the results. You will have a mathematics/statistics degree or be able to demonstrate a similarly strong background in a mathematically focused discipline. Also, experience in Python and SQL is required and a background in R or another language would also be advantageous. Key Responsibilities: Data Science Capability:
Contribute to the data science team by delivering Data Science projects for our customers. Pre-Sales and Bid Efforts:
Participate in pre-sales activities and bid processes, defining and explaining data science solutions while addressing client RFP (Request for Proposal) and ITT (Invitation to Tender) queries. Mentorship:
Act as a mentor to the data science team, fostering growth and development within the team, depending on seniority. Client Engagement:
Engage with clients to understand their requirements and deliver designs and outputs in the required formats. Required Skills & Experience: Proven expertise in AI/ML Techniques:
Extensive experience in applying artificial intelligence and machine learning techniques to solve complex problems and drive innovation. Proficiency in Programming Languages and Tools:
Demonstrable experience with programming languages and data science tools, including R, Python, Matlab, Spark, to develop and implement data-driven solutions. Cloud Platform Experience:
Strong background in working with major cloud platforms such as Google Cloud Platform (GCP), Amazon Web Services (AWS), and Microsoft Azure, leveraging their services for scalable and efficient data processing and analysis. ETL Development:
Experience in Extract, Transform, Load (ETL) development, designing and implementing data pipelines to ensure the smooth flow and integration of data across systems. Willingness to Travel:
Must be willing to travel as required to meet project and client needs. Good Communicator:
Able to take the initiative in keeping internal and external stakeholders informed. Able to communicate complex and technical topics to those outside of the discipline. Thought Leadership:
Demonstrated from a PhD, Chartered Status, R&D role or deeply innovative projects. MLOps:
Experience of delivery within an MLOps framework and able to tackle the challenges of delivery at scale. Multidisciplinary Working:
Evidence of working across fields or in joint project teams with other skill sets. Statistical and Mathematical Modelling:
Applied use of statistics and probability theory. Optimisation:
Experience of delivering optimisation solutions and familiarity with some of the techniques used. Advanced Data Engineering:
Understanding of data structures, architecture and deep understanding of building bespoke data pipelines.
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Eviden is an Atos Group business with an annual revenue of circa € 5 billion and a global leader in data-driven, trusted and sustainable digital transformation. As a next generation digital business with worldwide leading positions in digital, cloud, data, advanced computing and security, it brings deep expertise for all industries in more than 47 countries. By uniting unique high-end technologies across the full digital continuum with 55,000 world-class talents, Eviden expands the possibilities of data and technology, now and for generations to come. About the practice: The
DAA practice
represents a growing capability within Eviden and comprises a talented team of analysts, developers, consultants and architects covering all aspects of the information management lifecycle, from data management through to business intelligence and analytics. Eviden works with a range of large organisations facing an ever-increasing demand to realise greater value from their data, understand their business challenges, and are seeking the skills to develop advanced analytics, statistical modelling, and AI/ML routines. About the role: We are seeking a Data Scientist to undertake independent work, to play a role in the mentoring and development of the wider team, and to deliver data science projects, either individually or as part of a team. You will build machine learning pipelines for clients, frequently as part of a broader project involving scoping, gathering requirements, planning and interpretation of the results. You will have a mathematics/statistics degree or be able to demonstrate a similarly strong background in a mathematically focused discipline. Also, experience in Python and SQL is required and a background in R or another language would also be advantageous. Key Responsibilities: Data Science Capability:
Contribute to the data science team by delivering Data Science projects for our customers. Pre-Sales and Bid Efforts:
Participate in pre-sales activities and bid processes, defining and explaining data science solutions while addressing client RFP (Request for Proposal) and ITT (Invitation to Tender) queries. Mentorship:
Act as a mentor to the data science team, fostering growth and development within the team, depending on seniority. Client Engagement:
Engage with clients to understand their requirements and deliver designs and outputs in the required formats. Required Skills & Experience: Proven expertise in AI/ML Techniques:
Extensive experience in applying artificial intelligence and machine learning techniques to solve complex problems and drive innovation. Proficiency in Programming Languages and Tools:
Demonstrable experience with programming languages and data science tools, including R, Python, Matlab, Spark, to develop and implement data-driven solutions. Cloud Platform Experience:
Strong background in working with major cloud platforms such as Google Cloud Platform (GCP), Amazon Web Services (AWS), and Microsoft Azure, leveraging their services for scalable and efficient data processing and analysis. ETL Development:
Experience in Extract, Transform, Load (ETL) development, designing and implementing data pipelines to ensure the smooth flow and integration of data across systems. Willingness to Travel:
Must be willing to travel as required to meet project and client needs. Good Communicator:
Able to take the initiative in keeping internal and external stakeholders informed. Able to communicate complex and technical topics to those outside of the discipline. Thought Leadership:
Demonstrated from a PhD, Chartered Status, R&D role or deeply innovative projects. MLOps:
Experience of delivery within an MLOps framework and able to tackle the challenges of delivery at scale. Multidisciplinary Working:
Evidence of working across fields or in joint project teams with other skill sets. Statistical and Mathematical Modelling:
Applied use of statistics and probability theory. Optimisation:
Experience of delivering optimisation solutions and familiarity with some of the techniques used. Advanced Data Engineering:
Understanding of data structures, architecture and deep understanding of building bespoke data pipelines.
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