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

View Open Roles

Senior Data Scientist

Lear
Coventry
1 week ago
Create job alert

Senior Data Scientist

Coventry, UK

Company Overview

 Position overview:


We are seeking a Senior Data Scientist with a strong background in data collection and analysis, as well as advanced machine learning, deep learning knowledge. This role requires leading data science projects from conception to deployment, mentoring junior team members, and collaborating with stakeholders across departments. Expertise in Python, data engineering pipelines, MLOps, and production-grade model deployment is essential.

Main Missions:

Model development and deployment:

Develop end-to-end Data Science Projects with clear, actionable insights identified (from data ingestion to model deployment in production environments).


Drive the initiatives from ideation to design, building and deploying scalable models, deep learning architectures, defect detection, and NLP solutions.

Collaboration:

Work cross-functionally with business stakeholders to define project scope, objectives, and success metrics, translating business needs into solutions.


Define, along with the project manager and stakeholders’ input, the key technical success criteria for the solution and business process
Collaborate closely with the Data & Digitalization team to make sure there is an overall data strategy defined.
Partner with data engineering and Foundry teams to design scalable data pipelines.
Ensure adherence to data quality standards. Compliance to applicable security regulation, data privacy laws, EU-AI intelligence Act and other applicable according to the region where the solutions are developed and deployed.

Leadership and Mentorship:

Collaborate with other senior data scientists and mentor junior data scientists by providing technical guidance, defining necessary training to close skill gaps and supporting them during the development of their solutions.


Lead technical reviews and guide best practices in data science methodologies

Innovation:

Drive experimentation and model performance improvements.


Stay up to date in the latest technologies in ML and AI
Propose AI innovation projects that could solve observed business current challenges

 Key Skills and Qualifications:

Required Qualifications :

Master’s or PhD in Computer Science, Statistics, Engineering, or related field.


5+ years of experience in data science or ML.
Strong leadership and mentoring ability on technical subjects.
Excellent business and technical communication skills.
Strategic mindset with hands-on capability.
Proven experience as a Senior Data Scientist or Lead Data Scientist.
Proficiency in Python, R, SQL, and cloud platforms (AWS/Azure).
Hands-on with TensorFlow, PyTorch, or similar frameworks.
Experience in MLOps and scalable deployment.

Preferred Qualitfications :

Experience with big data tools (Spark, Hadoop).


Familiarity with business intelligence tools like Power BI or Tableau.
Published research or patents in AI/ML.

Why Lear

We offer a fantastic place to work that embraces diversity, opportunities for growth and the chance to be part of a company that puts its people first.

What We Offer

Competitive Salary,


Access to Learning and development opportunities.
Opportunities to give back to the community.
Meaningful work that makes a difference in the world

#LI-KE1

Related Jobs

View all jobs

Senior Data Scientist - Computer Vision

Senior Data Scientists

Senior Data Scientist

Senior Data Scientist

Senior Data Scientist

Senior Data Scientist

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.

Seasonal Hiring Peaks for Machine Learning Jobs: The Best Months to Apply & Why

The UK's machine learning sector has evolved into one of Europe's most intellectually stimulating and financially rewarding technology markets, with roles spanning from junior ML engineers to principal machine learning scientists and heads of artificial intelligence research. With machine learning positions commanding salaries from £32,000 for graduate ML engineers to £160,000+ for senior principal scientists, understanding when organisations actively recruit can dramatically accelerate your career progression in this pioneering and rapidly evolving field. Unlike traditional software engineering roles, machine learning hiring follows distinct patterns influenced by AI research cycles, model development timelines, and algorithmic innovation schedules. The sector's unique combination of mathematical rigour, computational complexity, and real-world application requirements creates predictable hiring windows that strategic professionals can leverage to advance their careers in developing tomorrow's intelligent systems. This comprehensive guide explores the optimal timing for machine learning job applications in the UK, examining how enterprise AI strategies, academic research cycles, and deep learning initiatives influence recruitment patterns, and why strategic timing can determine whether you join a groundbreaking AI research team or miss the opportunity to develop the next generation of machine learning algorithms.

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

Pre-employment screening in machine learning reflects the discipline's unique position at the intersection of artificial intelligence research, algorithmic decision-making, and transformative business automation. Machine learning professionals often have privileged access to proprietary datasets, cutting-edge algorithms, and strategic AI systems that form the foundation of organizational competitive advantage and automated decision-making capabilities. The machine learning industry operates within complex regulatory frameworks spanning AI governance directives, algorithmic accountability requirements, and emerging ML ethics regulations. Machine learning specialists must demonstrate not only technical competence in model development and deployment but also deep understanding of algorithmic fairness, AI safety principles, and the societal implications of automated decision-making at scale. Modern machine learning roles frequently involve developing systems that impact hiring decisions, financial services, healthcare diagnostics, and autonomous operations across multiple regulatory jurisdictions and ethical frameworks simultaneously. The combination of algorithmic influence, predictive capabilities, and automated decision-making authority makes thorough candidate verification essential for maintaining compliance, fairness, and public trust in AI-powered systems.

Why Now Is the Perfect Time to Launch Your Career in Machine Learning: The UK's Intelligence Revolution

The United Kingdom stands at the epicentre of a machine learning revolution that's fundamentally transforming how we solve problems, deliver services, and unlock insights from data at unprecedented scale. From the AI-powered diagnostic systems revolutionising healthcare in Manchester to the algorithmic trading platforms driving London's financial markets, Britain's embrace of intelligent systems has created an extraordinary demand for skilled machine learning professionals that dramatically exceeds the current talent supply. If you've been seeking a career at the forefront of technological innovation or looking to position yourself in one of the most impactful sectors of the digital economy, machine learning represents an exceptional opportunity. The convergence of abundant data availability, computational power accessibility, advanced algorithmic development, and enterprise AI adoption has created perfect conditions for machine learning career success.