Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Senior Data Scientist

Inizio Group
Manchester
3 weeks ago
Applications closed

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

About Inizio Medical
Inizio Medical is part of Inizio, the world’s leading healthcare and communications group. We are a trusted partner to pharmaceutical and healthcare clients, translating complex science into meaningful impact. Our division focuses on evidence-based communications and education for healthcare professionals and payers.

Overview of the Role
We are looking for a hands-on, entrepreneurial-minded Senior Data Scientist with a sense of curiosity to join our established team of Data Scientists, Data Analysts, and Insights Liaisons. Utilizing the latest in data science, AI, ML, and NLP, you will contribute to the Medical Analytics and Innovation Team’s efforts to measure key performance indicators, unearth insights, and generate actionable recommendations on behalf of clients and quantify the impact measures can have on business success.


You will partner with senior members of the Analytics and Insights Team to help build our practice by creating reusable tools for insight modelling and benchmarking (eg, tools to align content needs across multiple data assets, and applications to evaluate the effectiveness of medical affairs activities). You will collaborate with teams across Inizio Medical (Medical Analytics and Innovation, Artificial Intelligence/Data Engineering, Client Services, Medical Strategy, etc.). As a result, you will help us transform the client conversation from project outputs to portfolio outcomes and strategic insights.


Key Responsibilities
• Lead and deliver core data science projects independently, ensuring timely and high-quality outcomes.
• Design, build, evaluate, and optimize machine learning models to solve business problems and drive decision-making.
• Clean, transform, and manipulate complex datasets to prepare them for analysis and modeling.
• Ability to work with unstructured data in various formats (e.g., JSON, XML, TXT, PDF) stored in cloud environments such as Azure Blob Storage or Amazon S3, including extracting, cleaning, and analyzing relevant information.
• Develop actionable insights and recommendations from both quantitative and qualitative analyses and effectively communicate them to the Insights team and other stakeholders.
• Experience designing and developing reusable, scalable, and maintainable data pipelines to support end-to-end workflows—including data ingestion, transformation (ETL), and downstream analytics processes such as feature engineering, model training, and reporting.
• Identify opportunities to refine and improve analytical processes and proactively propose innovative solutions or seek collaborative input to enhance them.
• Contribute to the development of new client services and deliverables, leveraging data science capabilities to add value.
• Conduct rigorous validation and quality control checks to ensure the accuracy and reliability of data and analytical outputs.
• Assess and prioritize business needs and data requirements to align project goals with organizational objectives.
• Support a range of projects concurrently.
• Manage data science projects, including timeline estimation and the need for additional resources.

Individuals in this role will:
• Be proficient in statistical methods, hypothesis testing, and probability theory
• Stay updated on leading-edge tools, technologies, and methods in data analysis.
• Understand current data context, processes, and availability, and how current data processes and existing data can be leveraged to achieve the desired benefits
• Apply query, data exploration and transformation, and basic visualization techniques to create business insights or improve data quality
• Interpret results of analyses, identify trends and issues, and develop recommendations to support business objectives
• Communicate complex information in an easy-to-understand way and influence others to take action based on the useful information provided
• Demonstrate a curiosity and entrepreneurial mindset
• Collaborate with a team of subject matter experts

What you need to succeed:
• Bachelor’s and/or advanced degree in Statistics, Physics, Economics, Mathematics, Computer Science, or a related field
• Strong background in data science with 5+ years of experience, including experience applying AI, Machine Learning, and Natural Language Processing
• Technical proficiency: experience working with tools and technologies including programming language (eg, Python, R, SQL), data visualization tools (eg, PowerBI, Tableau), utilizing large language models (eg, ChatGPT, Claude, Gemini), experience working with unstructured data in Blob and S3 storage
• Strong foundation in statistical methods and machine learning, including experience with big data processing, predictive modeling, regression techniques, and applying ML/NLP algorithms for tasks such as classification, clustering, entity recognition, and text analysis.
• Cloud platform use: experience working with cloud platforms (e.g., AWS, Azure, GCP) and version control tools such as Git, Bitbucket, or similar.
• Communication skills: able to communicate their findings and insights clearly and effectively to both technical and non-technical audiences
• Problem-solving skills: ideal candidate should be able to identify problems and develop solutions to improve processes and decision-making based on data
• Attention to detail to ensure accuracy and completeness of data analysis
• Experience with machine learning and natural language processing algorithms
• Understanding of the digital application development cycle, from concept to deployment and iterative refinement
• The ability to work on complex projects of large scope
• The ability to complete work independently after receiving general guidance on new projects
• High degree of intellectual curiosity and ability to absorb new concepts quickly and apply to real world situations
• Proactive contributor in all settings; autonomously, remote, in-office, in team meetings, with clients, in planning and in execution


Preferable Skills
• Experience working with tools and technologies Hadoop, Spark, TensorFlow, Apache
• Prior experience working in healthcare, pharmaceuticals, biotech industry
• Familiarity with the application development life cycle and best practices in software deployment

What We Offer
• Competitive salary and benefits package, including private medical insurance and company retirement plan
• Flexible, remote-first working environment with occasional travel
• The opportunity to work on cutting-edge, impactful AI projects within a global leader in healthcare communications
• A friendly and informal culture that values curiosity, collaboration, and continuous learning


Ready to Apply?
If you’re passionate about deploying data science and AI for real-world impact and thrive in a fast-paced, mission-driven environment, we’d love to hear from you.

Don't meet every job requirement? That's okay! Our company is dedicated to building a diverse, inclusive, and authentic workplace. If you're excited about this role, but your experience doesn't perfectly fit every qualification, we encourage you to apply anyway. You may be just the right person for this role or others.

Create a Job Alert

Interested in building your career at Inizio? Get future opportunities sent straight to your email.

Apply for this job

*

indicates a required field

First Name *

Last Name *

Email *

Phone *

Resume/CV *

Enter manually

Accepted file types: pdf, doc, docx, txt, rtf

Enter manually

Accepted file types: pdf, doc, docx, txt, rtf


#J-18808-Ljbffr

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 Machine Learning Jobs: Careers That Don’t Exist Yet

Machine learning (ML) has become one of the most powerful forces reshaping the modern world. From voice assistants and recommendation engines to fraud detection and medical imaging, it underpins countless applications. ML is no longer confined to research labs—it powers business models, public services, and consumer technologies across the globe. In the UK, demand for machine learning professionals has risen dramatically. Organisations in finance, retail, healthcare, and defence are embedding ML into their operations. Start-ups in Cambridge, London, and Edinburgh are pioneering innovations, while government-backed initiatives aim to position the UK as a global AI leader. Salaries for ML engineers and researchers are among the highest in the tech sector. Yet despite its current importance, machine learning is only at the beginning of its journey. Advances in generative AI, quantum computing, robotics, and ethical governance will reshape the profession. Many of the most vital machine learning jobs of the next two decades don’t exist today. This article explores why new careers will emerge, the roles likely to appear, how today’s roles will evolve, why the UK is well positioned, and how professionals can prepare now.

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.