Senior Data Scientist

Senior Data Scientist

London Full-Time 48000 - 72000 £ / year (est.) No home office possible
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At a Glance

  • Tasks: Lead data projects, build predictive models, and analyze health disparities to improve patient care.
  • Company: Join the HEU, an NHS consultancy dedicated to enhancing healthcare through data-driven insights.
  • Benefits: Collaborate with a dynamic team, gain mentorship, and contribute to impactful healthcare solutions.
  • Why this job: Make a real difference in healthcare while developing your data science skills in a supportive environment.
  • Qualifications: Master's degree in STEM or equivalent experience; strong coding skills in SQL or Python required.
  • Other info: Opportunity to mentor junior team members and engage directly with clients.

The predicted salary is between 48000 - 72000 £ per year.

Job summary

The senior data scientist / econometrician provides vital data and insights to inform decisions, driving improvements in healthcare and impacting millions of people. You will work on and lead the delivery of a range of projects, focusing on data and analytical aspects. You will provide specialist advice and guidance on the use of data and analytics to the HEU, informing how we deliver projects and achieve clients’ aims. You will work on various research projects as commissioned by our clients under a consultancy model, which will take up to 80% of your time (this may change as the work of the unit evolves).

Main duties of the job

Plan, organise, and lead data and analytics aspects of projects. Responsibilities include:

  1. Building predictive models for admissions/discharges to optimise resources and reduce bottlenecks in emergency departments.
  2. Analysing health disparities across populations, identifying factors like socio-economic status or access to care.
  3. Applying NLP to unstructured data (e.g., clinician notes, patient feedback) for insights into patient needs.
  4. Using machine learning to predict outcomes such as readmission rates or disease progression, supporting proactive care.
  5. Developing econometric models to evaluate healthcare policy effects on patient health, utilisation, and costs.
  6. Analysing complex datasets, identifying trends, and selecting methods for data cleaning, processing, and analysis.
  7. Addressing unique questions, developing innovative approaches to client needs.
  8. Following and contributing to best practices in data analysis.
  9. Managing software for statistical analysis, including procuring and implementing improvements.
  10. Developing and implementing policies for HEU and CSU teams.
  11. Quality-assuring team outputs.
  12. Acting independently as a subject-matter expert within guidelines.
  13. Supporting business development and contributing to data science proposals by scoping projects and estimating costs.

About us

The HEU is an NHS consultancy of 17 team members across three teams: Health Economics, Service Delivery and Data and Analytics.

You will sit within the data and analytics team, led by the chief analyst and reporting to the lead data scientist/econometrician.

During projects you will work closely across the HEU team, with data scientists, analysts, project managers, and health economists.

You will engage with our clients, partners and stakeholders throughout projects, understanding their needs and communicating your work.

Job description

Job responsibilities

Key responsibilities

Data science function

  1. Plan, organise and deliver the data and analytic aspects of projects, including in a project leadership role.
  2. Building predictive models to forecast patient admissions and discharges, helping optimise hospital resources and reduce bottlenecks in areas like emergency departments.
  3. Analysing disparities in health outcomes across different populations, identifying factors like socio-economic status, geography, or access to care that contribute to inequalities.
  4. Applying NLP techniques to unstructured text data, such as clinician notes or patient feedback, to extract key information and improve understanding of patient needs and outcomes.
  5. Using supervised and unsupervised machine learning techniques to predict outcomes such as readmission rates, disease progression, or patient deterioration, aiding proactive care.
  6. Developing econometric models to evaluate the effects of healthcare policies or interventions on key outcomes, such as patient health, hospital utilisation, or treatment costs.
  7. Analyse complex datasets to identify trends and patterns, and apply statistical models to solve business problems.
  8. Work on novel issues and questions which may not have precedent about how they have been tackled before.
  9. Follow data analysis and econometrics best practices and contribute to the ongoing development and improvement of these.
  10. Manage systems and software used to deliver statistical analysis and other functions as required for projects.
  11. Propose and develop policies and procedures relating to data and analytics.
  12. Appraise and quality assure the analytical outputs from the team.
  13. Act as a specialist in own area and achieve own objectives.
  14. Undertake business development meetings, supported by colleagues.

Team-working

  1. Provide guidance and mentorship to junior team members.
  2. Support the lead data scientist / econometrician to line manage other members of the team.
  3. Supervise the completion of tasks by others.
  4. Proactively provide training and share knowledge on areas of expertise to the wider unit.
  5. Deliver training to clients on own area of expertise.

Communication and networking

  1. Communicate and present complex information and insights to non-technical stakeholders.
  2. Write high-quality reports which effectively communicate our findings.
  3. Synthesize multiple sources to communicate on complex issues.
  4. Understand client needs and objectives.
  5. Make judgements where there are conflicting views.

Project and financial management

  1. Lead on small to medium sized projects and work with others to deliver projects to time, scope, budget and quality.
  2. Plan and organise complex data analysis tasks.
  3. Manage project budgets.
  4. Horizon-scan and identify potential issues before they occur.

Person Specification
Experience
Essential

  1. Masters degree in a related STEM subject or equivalent level of experience.
  2. Varied experience of extracting data, manipulating, understanding, transforming, wrangling, cleaning, and storing health data.
  3. Ability to write well-designed code (e.g. SQL or Python).
  4. Possess foundational knowledge in data science, statistical analysis, and machine learning techniques.
  5. Varied experience working in data and analytics functions in the NHS.

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Senior Data Scientist employer: Midlands and Lancashire Commissioning Support Unit

At HEU, we pride ourselves on being an exceptional employer, offering a collaborative and innovative work culture that empowers our Senior Data Scientists to make a real impact in healthcare. With a strong focus on professional development, our team members benefit from mentorship opportunities and the chance to lead diverse projects that drive meaningful change for millions. Located within the NHS framework, we provide a unique environment where your expertise in data analytics can flourish, supported by a commitment to best practices and continuous improvement.
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Contact Detail:

Midlands and Lancashire Commissioning Support Unit Recruiting Team

StudySmarter Expert Advice 🤫

We think this is how you could land Senior Data Scientist

✨Tip Number 1

Familiarize yourself with the latest trends in healthcare data analytics. Understanding current challenges and innovations in the field will help you demonstrate your expertise during interviews and discussions.

✨Tip Number 2

Network with professionals in the healthcare analytics space. Attend relevant conferences or webinars to connect with potential colleagues and learn about their experiences, which can provide valuable insights for your application.

✨Tip Number 3

Showcase your experience with predictive modeling and machine learning techniques. Be prepared to discuss specific projects where you've successfully applied these skills, as they are crucial for the role.

✨Tip Number 4

Prepare to communicate complex data insights to non-technical stakeholders. Practice explaining your past projects in simple terms, as effective communication is key in this role.

We think you need these skills to ace Senior Data Scientist

Predictive Modeling
Data Analysis
Machine Learning
Natural Language Processing (NLP)
Econometric Modeling
Statistical Analysis
Data Cleaning and Processing
Project Management
Communication Skills
Team Leadership
Client Engagement
Report Writing
SQL Programming
Python Programming
Problem-Solving Skills
Quality Assurance

Some tips for your application 🫡

Tailor Your CV: Make sure your CV highlights relevant experience in data science, statistical analysis, and machine learning techniques. Emphasize any projects where you've built predictive models or worked with complex datasets, as these are key responsibilities for the role.

Craft a Compelling Cover Letter: In your cover letter, express your passion for healthcare analytics and how your skills align with the company's mission. Mention specific experiences that demonstrate your ability to lead projects and provide insights that drive improvements in healthcare.

Showcase Technical Skills: Clearly outline your proficiency in programming languages like SQL and Python. Provide examples of how you've applied these skills in previous roles, particularly in relation to data manipulation and analysis.

Highlight Team Collaboration: Since the role involves working closely with various teams, mention any past experiences where you successfully collaborated with others. Discuss how you provided guidance or mentorship to junior team members, as this is an important aspect of the position.

How to prepare for a job interview at Midlands and Lancashire Commissioning Support Unit

✨Showcase Your Technical Skills

Be prepared to discuss your experience with SQL, Python, and machine learning techniques. Highlight specific projects where you've built predictive models or applied NLP to unstructured data, as these are crucial for the role.

✨Demonstrate Your Problem-Solving Abilities

Prepare examples of how you've tackled complex datasets and unique questions in previous roles. Discuss your approach to identifying trends and applying statistical models to solve business problems.

✨Communicate Effectively

Practice explaining complex data insights in a way that non-technical stakeholders can understand. This will be key in demonstrating your ability to synthesize information and communicate findings clearly.

✨Emphasize Team Collaboration

Highlight your experience working in teams, especially in a consultancy environment. Be ready to discuss how you've mentored junior team members and contributed to a collaborative work culture.

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