Senior Data Science Manager.

Medtronic
London
11 months ago
Applications closed

Related Jobs

View all jobs

Data Science Manager (Metaheuristics)

Data Science Manager – Gen/AI & ML Projects - Bristol

Data Science Manager

Analytics Engineering Manager

Senior Manager (Data Science)

Pricing Data Science Manager

Careers that Change Lives 
Medtronic-Digital Technologies is creating ambitious new products that bring connectivity, real-time guidance, and decision support to the operating room. To support this mission, we are developing compact, high-performance, embedded systems that enable edge computing and connectivity. 

Working closely with other teams across Medtronic, we are creating a connected ecosystem and leveraging the state of the art in computer vision to provide the most comprehensive view of surgery. If you’re interested in using cutting-edge technology to improve the standard of care in surgery on a global scale, this could be the place for you.

A Day in the Life 
As a Data Science Manager, you will be responsible for:

• Managing a team of data analysts and data scientists within the Surgical Operating Unit at Medtronic. 
• Building advanced analytics and leading technical initiatives to shape the data culture within Medtronic. 
• Guiding the team in using statistical and predicative methods to understand customer behaviour and product performance. 
• Ensuring professional development of the team and advancing technical capabilities.

Must Haves 
• MSc or PhD in a Science, Engineering, Technology and Mathematics (STEM) subject 
• A solid grounding in Structured Query Language (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 
• In-depth knowledge of statistical and machine learning models
• Experience in writing clean and maintainable code for collaborative working and using code versioning tools 
• Excellent communicator and experience with stakeholder management, comfortable talking with programmers, marketers, surgeons, business leaders, and everyone in-between 
• Self–starter mindset, ability to proactively identify issues and opportunities for improvement 
Experience of and ability to effectively use cloud native data science tooling
• Extensive experience with Tableau and data build tool (dbt) or similar tooling

Nice to Haves
• Knowledge of data compliance including General Data Protection Regulation (GDPR), Health Insurance Portability and Accountability Act (HIPAA) and Service Organization Control Type 2 (SOC2) compliance policies 
• Previous experience managing teams of data analysts or data scientists
• Experience in integration of highly heterogeneous data streams (IoT data, customer interactions, product metrics). 

We Offer
We offer a competitive salary and benefits package to all our employees:
• Flexible working environment
• Annual Incentive Plan % depending on company results
• Pension scheme and group discount on healthcare insurance 
• Training possibilities via Cornerstone/Skills Lab
• Employee Assistance Program and Recognize! (our global recognition program)

Our Commitment
Our unwavering commitment to inclusion, diversity, and equity (ID&E) means zero barriers to opportunity within Medtronic and a culture where all employees belong, are respected, and feel valued for who they are and the life experiences they contribute. We know equity starts beyond our workplace, and we must play a role in addressing systemic inequities in our communities if we hope to have long-term sustainable impact. Anchored in our Mission, we continue to drive ID&E forward both to enhance the well-being of Medtronic employees and to accelerate innovation that brings our lifesaving technologies to more people in more places around the world. 

Get the latest insights and jobs direct. Sign up for our newsletter.

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

Industry Insights

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

Negotiating Your Machine Learning Job Offer: Equity, Bonuses & Perks Explained

How to Secure a Compensation Package That Matches Your Technical Mastery and Strategic Influence in the UK’s ML Landscape Machine learning (ML) has rapidly shifted from an emerging discipline to a mission-critical function in modern enterprises. From optimising e-commerce recommendations to powering autonomous vehicles and driving innovation in healthcare, ML experts hold the keys to transformative outcomes. As a mid‑senior professional in this field, you’re not only crafting sophisticated algorithms; you’re often guiding strategic decisions about data pipelines, model deployment, and product direction. With such a powerful impact on business results, companies across the UK are going beyond standard salary structures to attract top ML talent. Negotiating a compensation package that truly reflects your value means looking beyond the numbers on your monthly payslip. In addition to a competitive base salary, you could be securing equity, performance-based bonuses, and perks that support your ongoing research, development, and growth. However, many mid‑senior ML professionals leave these additional benefits on the table—either because they’re unsure how to negotiate them or they simply underestimate their long-term worth. This guide explores every critical aspect of negotiating a machine learning job offer. Whether you’re joining an AI-focused start-up or a major tech player expanding its ML capabilities, understanding equity structures, bonus schemes, and strategic perks will help you lock in a package that matches your technical expertise and strategic influence. Let’s dive in.

Machine Learning Jobs in the Public Sector: Opportunities Across GDS, NHS, MOD, and More

Machine learning (ML) has rapidly moved from academic research labs to the heart of industrial and governmental operations. Its ability to uncover patterns, predict outcomes, and automate complex tasks has revolutionised industries ranging from finance to retail. Now, the public sector—encompassing government departments, healthcare systems, and defence agencies—has become an increasingly fertile ground for machine learning jobs. Why? Because government bodies oversee vast datasets, manage critical services for millions of citizens, and must operate efficiently under tight resource constraints. From using ML algorithms to improve patient outcomes in the NHS, to enhancing cybersecurity within the Ministry of Defence (MOD), there’s a growing demand for skilled ML professionals in UK public sector roles. If you’re passionate about harnessing data-driven insights to solve large-scale problems and contribute to societal well-being, machine learning jobs in the public sector offer an unparalleled blend of challenge and impact. In this article, we’ll explore the key reasons behind the public sector’s investment in ML, highlight the leading organisations, outline common job roles, and provide practical guidance on securing a machine learning position that helps shape the future of government services.

Contract vs Permanent Machine Learning Jobs: Which Pays Better in 2025?

Machine learning (ML) has swiftly become one of the most transformative forces in the UK technology landscape. From conversational AI and autonomous vehicles to fraud detection and personalised recommendations, ML algorithms are reshaping how organisations operate and how consumers experience products and services. In response, job opportunities in machine learning—including roles in data science, MLOps, natural language processing (NLP), computer vision, and more—have risen dramatically. Yet, as the demand for ML expertise booms, professionals face a pivotal choice about how they want to work. Some choose day‑rate contracting, leveraging short-term projects for potentially higher immediate pay. Others embrace fixed-term contract (FTC) roles for mid-range stability, or permanent positions for comprehensive benefits and a well-defined career path. In this article, we will explore these different employment models, highlighting the pros and cons of each, offering sample take‑home pay scenarios, and providing insights into which path might pay better in 2025. Whether you’re a new graduate with a machine learning degree or an experienced practitioner pivoting into an ML-heavy role, understanding these options is key to making informed career decisions.