Data Scientist

Bluetownonline
Manchester
1 month ago
Applications closed

Related Jobs

View all jobs

Data Scientist

Data Scientist

Data Scientist

Data Scientist

Data Scientist / AI Engineer (TensorFlow, PyTorch)

Data Scientist 80k

Job Title:Data Scientist

Location:Manchester

Salary:£46,148 to £60,809 DOE

Job type:Full Time, Permanent

Job Summary:

We are seeking a talented and highly motivated Data Scientist to join our team at the NHD. As a Data Scientist, you will play a key role in analysing and interpreting complex healthcare data to drive evidence-based decision-making and improve patient outcomes.

We have an exciting full-time opportunity available for an experience and promising Data Scientist at the National Haemophilia Database (NHD), to play a key role in analysing and interpreting complex healthcare data to drive evidence-based decision-making and improve patient outcomes.

The (NHD) is a register of people in the UK with all types of bleeding disorders started in 1969. Its purpose is to study the complete national cohort of patients with these conditions and improve the care of people with bleeding disorders. The database is held within the NHS and managed by the UK Haemophilia Centre Doctors’ Organisation (UKHCDO) which is an association of medical practitioners who work within the NHS Haemophilia Centre’s of England, Scotland, Northern Ireland, or Wales and have an interest in the care of people with Haemophilia or other inherited bleeding disorders.

NHD is at a transformation stage in its development and requires insight professionals to harness the wealth of data that is available to it. The NHD has the richest data store for bleeding disorders in the world and are investing heavily in the infrastructure required to enhance the processing, accessibility and surfacing of that data. What we now require is an individual that can harness the power of that data and convert it into insights and information that can make a real difference to the lives of people with bleeding disorders:

You would be working with the UKs best clinical, scientific, and statistical capabilities in this sector, whilst managing a small team. Would you enjoy being part of an NHD team that values, recognises, and celebrates staff members, their skills, and contributions? Could you play an invaluable part in a team to provide a high-level service to the NHS, work in partnership with the pharmaceutical sector who research and produce the current and future products for people with bleeding disorders, and ultimately, working with these partners, improve the lives of people with bleeding disorders? If yes, the National Haemophilia Database is the place for you.

Responsibilities:

Data Analysis: Perform data exploration, cleaning, and analysis on large healthcare datasets to derive meaningful insights and identify patterns. Predictive Modelling: Develop and implement predictive models to forecast patient outcomes, disease trends, and resource utilisation. Data Visualisation: Create visually compelling and easy-to-understand data visualisations to communicate findings and support data-driven decisions. Machine Learning: Utilise machine learning techniques to develop algorithms and models for various healthcare applications. Data Integration: Integrate disparate data sources to build comprehensive and holistic healthcare datasets for analysis. Collaborate with Healthcare Professionals: Work closely with clinicians and healthcare professionals to understand their data needs and provide data-driven solutions. Research Support: Assist in research projects by providing data expertise, statistical analysis, and interpretation of results. Continuous Improvement: Stay updated with the latest data science methodologies, tools, and technologies, and propose innovative approaches to enhance data analysis capabilities.

Requirements:

Education: Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, or a related field. Experience: Proven experience as a Data Scientist in the healthcare domain, preferably within the NHS or a healthcare setting. Technical Skills: Proficiency in programming languages such as Python, R, or SQL, and experience with data manipulation and analysis tools. Statistical Knowledge: Strong statistical and quantitative analysis skills, including experience with statistical modelling and hypothesis testing. Data Visualisation: Ability to create interactive and informative data visualisations using tools such as Tableau or Power BI. Machine Learning: Familiarity with machine learning algorithms and frameworks for classification, regression, and clustering tasks. Communication: Excellent communication and presentation skills to effectively convey complex data insights to non-technical stakeholders.

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.

Careers

Navigating Machine Learning Career Fairs Like a Pro: Preparing Your Pitch, Questions to Ask, and Follow-Up Strategies to Stand Out

Machine learning (ML) has swiftly become one of the most in-demand skill areas across industries, with companies leveraging predictive models and data-driven insights to solve challenges in healthcare, finance, retail, manufacturing, and beyond. Whether you’re an early-career data scientist aiming to break into ML, a seasoned engineer branching into deep learning, or a product manager exploring AI-driven solutions, machine learning career fairs offer a powerful route to connect with prospective employers face-to-face. Attending these events can help you: Network with hiring managers and technical leads who make direct recruitment decisions. Gain insider insights on the latest ML trends and tools. Learn about emerging job roles and new industry verticals adopting machine learning. Showcase your interpersonal and communication skills, both of which are increasingly important in collaborative AI/ML environments. However, with many applicants vying for attention in a bustling hall, standing out isn’t always easy. In this detailed guide, we’ll walk you through how to prepare meticulously, pitch yourself confidently, ask relevant questions, and follow up effectively to land the machine learning opportunity that aligns with your ambitions.

Jobs

Common Pitfalls Machine Learning Job Seekers Face and How to Avoid Them

Machine learning has emerged as one of the most sought-after fields in technology, with companies across industries—from retail and healthcare to finance and manufacturing—embracing data-driven solutions at an unprecedented pace. In the UK, the demand for skilled ML professionals continues to soar, and opportunities in this domain are abundant. Yet, amid this growing market, competition for machine learning jobs can be fierce. Prospective employers set a high bar: they seek candidates with not just theoretical understanding, but also strong practical skills, business sense, and an aptitude for effective communication. Whether you’re a recent graduate, a data scientist transitioning into machine learning, or a seasoned developer pivoting your career, it’s essential to avoid common mistakes that may hinder your prospects. This blog post explores the pitfalls frequently encountered by machine learning job seekers, and offers actionable guidance on how to steer clear of them. If you’re looking for roles in this thriving sector, don’t forget to check out Machine Learning Jobs for the latest vacancies across the UK. In this article, we’ll break down these pitfalls to help you refine your approach in applications, interviews, and career development. By taking on board these insights, you can significantly enhance your employability, stand out from the competition, and secure a rewarding position in the world of machine learning.

Careers

Career Paths in Machine Learning: From Entry-Level Roles to Leadership and Beyond

Machine learning has rapidly transformed from an academic pursuit to a cornerstone of modern technology, fueling innovations in healthcare, finance, retail, cybersecurity, and virtually every industry imaginable. From predictive analytics and computer vision to deep learning models that power personalisation algorithms, machine learning (ML) is reshaping business strategies and creating new economic opportunities. As demand for ML expertise continues to outstrip supply, the UK has become a vibrant hub for machine learning research, entrepreneurship, and corporate adoption. Whether you’re just starting out or have experience in data science, software development, or adjacent fields, there has never been a better time to pursue a career in machine learning. In this article, we will explore: The growing importance of machine learning in the UK Entry-level roles that can kick-start your ML career The skills and qualifications you’ll need to succeed Mid-level and advanced positions, including leadership tracks Tips for job seekers on www.machinelearningjobs.co.uk By the end, you’ll have a clear view of how to build, grow, and lead in one of the most exciting fields in modern technology.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.