Engineer the Quantum RevolutionYour expertise can help us shape the future of quantum computing at Oxford Ionics.

View Open Roles

Data Science Manager, Digital Technologies

Medtronic
Greater London
1 week ago
Create job alert

At Medtronic you can begin a life-long career of exploration and innovation, while helping champion healthcare access and equity for all. You’ll lead with purpose, breaking down barriers to innovation in a more connected, compassionate world.

A Day in the Life

The Digital Technologies Business Unit (DTBU) at Medtronic is implementing cutting-edge AI technology, computer vision, and augmented reality in the operating room (OR) to augment surgical coaching, and eventually, performance. Our goal is to deliver safer surgery around the world.

Our Touch SurgeryTM Video solution is an innovative video management and data analytics platform for hospitals that includes the DS1 Computer, our first OR device, allowing surgeons, OR team members, and trainees to securely access videos of their procedures shortly after surgery.

Responsibilities may include the following and other duties may be assigned:

Manage a team of data scientists within the Surgical Operating Unit at Medtronic. Lead advanced analytics initiatives to foster a data-driven culture within Medtronic. Act as a key stakeholder in the design and development of data infrastructure and models. Guide the team in applying statistical and predictive methods to analyze customer behavior and product performance. Oversee the development and productization of data products, delivering actionable insights to customers. Support the professional development of team members and strengthen their technical capabilities. Drive innovation and continuous improvement in data practices and analytics strategies.

Required Knowledge and Experience:

MSc or PhD in a STEM subject.  Previous experience managing teams of data scientists.  A solid grounding in SQL with a good understanding of best practices in software engineering and data engineering.  Practical object-oriented programming experience in Python with knowledge of relevant packages including Pandas, NumPy, SciPy, Matplotlib, Scikit-learn, Pytorch.  In-depth knowledge of statistical and machine learning models as well as experience with end-to-end delivery lifecycles.  Experience in writing clean and maintainable code for collaborative working and using code versioning tools.  Excellent communicator and experience with stakeholder management. Self–starter mindset – you can proactively identify issues and opportunities for improvement.  Experience of and ability to effectively use cloud native data science tooling. Extensive experience with Tableau and dbt or similar tooling.

Ideally, you will bring knowledge of data compliance frameworks, including GDPR, HIPAA, and SOC2 policies. Experience integrating highly heterogeneous data streams—such as IoT data, customer interactions, and product performance metrics—is also valuable. Additionally, domain knowledge in health technology or surgical practice would be a strong asset.

Physical Job Requirements

The above statements are intended to describe the general nature and level of work being performed by employees assigned to this position, but they are not an exhaustive list of all the required responsibilities and skills of this position. 

Benefits & Compensation

Medtronic offers a competitive Salary and flexible Benefits Package
A commitment to our employees lives at the core of our values. We recognize their contributions. They share in the success they help to create.We offer a wide range of benefits, resources, and competitive compensation plans designed to support you at every career and life stage.
 

This position is eligible for a short-term incentive called the Medtronic Incentive Plan (MIP).

About Medtronic

We lead global healthcare technology and boldly attack the most challenging health problems facing humanity by searching out and finding solutions.
Our Mission — to alleviate pain, restore health, and extend life — unites a global team of 95,000+ passionate people. 
We are engineers at heart— putting ambitious ideas to work to generate real solutions for real people. From the R&D lab, to the factory floor, to the conference room, every one of us experiments, creates, builds, improves and solves. We have the talent, diverse perspectives, and guts to engineer the extraordinary.

Learn more about our business, mission, and our commitment to diversity
 

Related Jobs

View all jobs

Engineering Lead Manager, Data Science

Data Architect

Data Architect

Data Architect

Business Intelligence Manager

Business Intelligence Manager

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

The Future of Data Science Jobs: Careers That Don’t Exist Yet

Data science has rapidly become one of the most influential disciplines of the digital age. Once a niche combination of statistics and computing, it is now central to how organisations innovate, compete, and grow. From healthcare and finance to retail, logistics, and government, data science is reshaping decision-making across every sector. In the UK, data science has grown into a core career pathway. Salaries are competitive, demand continues to rise, and roles now extend far beyond analytics into artificial intelligence, machine learning, and predictive modelling. Yet as technologies evolve, many of the most important data science careers of the future don’t exist today. This article explores why entirely new roles will emerge, the kinds of careers that may appear, how existing jobs will evolve, why the UK is well placed to lead, and what professionals can do to prepare for this transformation.

Seasonal Hiring Peaks for Data Science Jobs: The Best Months to Apply & Why

The UK's data science sector has matured into one of Europe's most intellectually rewarding and financially attractive technology markets, with roles spanning from junior data analysts to principal data scientists and heads of artificial intelligence. With data science positions commanding salaries from £30,000 for graduate data analysts to £140,000+ for senior principal scientists, understanding when organisations actively recruit can dramatically accelerate your career progression in this intellectually stimulating and rapidly evolving field. Unlike traditional analytical roles, data science hiring follows distinct patterns influenced by business intelligence cycles, research funding schedules, and machine learning project timelines. The sector's unique combination of mathematical rigour, business impact requirements, and cutting-edge technology adoption creates predictable hiring windows that strategic professionals can leverage to advance their careers in extracting insights from tomorrow's data. This comprehensive guide explores the optimal timing for data science job applications in the UK, examining how enterprise analytics strategies, academic research cycles, and artificial intelligence initiatives influence recruitment patterns, and why strategic timing can determine whether you join a pioneering AI research team or miss the opportunity to develop the next generation of intelligent systems.

Pre-Employment Checks for Data Science Jobs: DBS, References & Right-to-Work and more Explained

Pre-employment screening in data science reflects the discipline's unique position at the intersection of statistical analysis, machine learning innovation, and strategic business intelligence. Data scientists often have privileged access to comprehensive datasets, proprietary algorithms, and business-critical insights that form the foundation of organisational strategy and competitive positioning. The data science industry operates within complex regulatory frameworks spanning GDPR, sector-specific data protection requirements, and emerging AI governance regulations. Data scientists must demonstrate not only technical competence in statistical modelling and machine learning but also deep understanding of research ethics, data privacy principles, and the societal implications of algorithmic decision-making. Modern data science roles frequently involve analysing personally identifiable information, financial data, healthcare records, and sensitive business intelligence across multiple jurisdictions and regulatory frameworks simultaneously. The combination of analytical privilege, predictive capabilities, and strategic influence makes thorough candidate verification essential for maintaining compliance, security, and public trust in data-driven insights and automated systems.