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- Tasks: Design and implement advanced machine learning solutions for real-world healthcare challenges.
- Company: Join a leading global provider of clinical research and healthcare intelligence.
- Benefits: Hybrid work model, diverse career paths, and a collaborative team environment.
- Other info: Be part of a diverse team that values innovation and personal growth.
- Why this job: Make a real impact on patient care using cutting-edge technology and data science.
- Qualifications: MSc or PhD in relevant fields with experience in machine learning and data analysis.
The predicted salary is between 28800 - 48000 £ per year.
Data Scientist
ACOE,Patient & Practitioner Analytics
Paddington, London (Hybrid)
We are looking for a creative, innovative, intellectually curious and entrepreneurial Data Scientist with experience in developing Machine Learning solutions to join our London-based team.
This is an exciting opportunity to work in one of the world\’s leading human data science teams working with Real World Insights to help our clients answer specific questions globally, make more informed decisions and deliver results.
The role
We are looking for a Data Scientist who will play a pivotal role in designing and implementing advanced analytical solutions for complex challenges in the life science domains. The primary focus of the role will be to design and apply cutting-edge machine learning techniques to extract meaningful insights from large-scale, real-world medical data, helping to inform and improve healthcare outcomes. This role requires a strong ability to interpret diverse datasets, identify the most suitable analytical approaches, and deliver robust solutions to tackle multifaceted business problems.
You will be using existing machine learning tools and will be responsible for tailoring them as business problems require. As part of this role, you will also be interacting with internal and external stakeholders from different backgrounds, therefore good technical and non-technical communication skills are crucial.
In addition, the role offers a scope for development in other key areas
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Product Development – collaborating with software engineers, system architects, and fellow data scientists to build scalable, automated routines and libraries.
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Business Development – contribute to business development initiatives through technical support for demos, thought leadership (e.g. publications, academic presentations, workshops), and input on project proposals.
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Client Engagement – engage in delivering tailored solutions, generating reports, and communicating findings effectively to meet client needs.
At IQVIA we appreciate and nurture individual talent. Therefore, the exact blend of responsibilities and individual career development will depend in part on the skill set and aspirations of the successful candidate.
Our ideal candidate: Experience
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MSc or PhD in Machine Learning, Computer Science, Physics, Bioinformatics or similar.
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Analytical experience within a top academic or commercial organisation where data-led problem solving was a core part of the role.
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Experience with the design and delivery of advanced machine learning projects in either academic or commercial settings.
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Experience solving problems within commercial life science and healthcare (e.g. prediction of health outcomes such as disease progression, line of therapy, market sizing, etc.)
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A proactive, innovative and pragmatic approach to problem solving and an ability to think critically and independently. Ability to work as part of a cross-functional team.
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Experience with software development lifecycle, particularly using GitLab.
Our ideal candidate: Skills
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Experienced in handling Big Data.
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Deep knowledge of machine learning methods, particularly gradient boosting classifiers (e.g. XGBoost, LightGBM).
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Capable of developing and using AutoML tools.
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Well versed in explainability methods (e.g. SHAP, LIME, ELI5).
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Skilled in Python/R and SQL.
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Proficient in using data science packages (e.g. sklearn, pandas, matplotlib, etc.).
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Exposure to GenAI technologies, including but not limited to prompt engineering and Agentic AI.
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Ability to write clean and documented code, as well as understanding and modifying existing code bases.
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Demonstrated ability to communicate complex analytical concepts and insights to both technical and non-technical audiences.
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Demonstrated creativity, critical thinking, project planning, and attention to detail capabilities.
Bonus points for:
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Knowledge of pharmaceutical market and experience with pharmaceutical data (medical, hospital, pharmacy, claims data).
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Familiar with using Linux terminal & containers (e.g. Docker).
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Knowledge of deep learning methods (e.g. CNNs, RNNs, Transformer).
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Knowledge of epidemiology / biostatistics, particularly analytical issues relating to studies of treatment effectiveness, disease progression, adherence, healthcare utilization, etc.
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Knowledge of healthcare / life science issues involving Real-World Evidence.
The Team
You will join a high-profile team to work on an artificial intelligence driven predictive analytics software solution. This platform delivers data-driven insights primarily focused on assessing the impact and value of evidence as well as how to optimize evidence strategy. Commercial Solutions are embedded within software which facilitates interpretation of the predictions, informed stakeholder prioritization discussions, and enhanced decision making.
We are serious about healthcare software. We have a dedicated, collaborative team with meaningful shared goals who can use the most cutting-edge technology, the largest data sets, and the best analytics tools to achieve them. And we have fun on the journey! We invite you to be part of a recognized global leader willing to challenge the status quo to improve patient care. You will be in good company, amongst some of the finest minds in Technology and Healthcare.
Why Join?
You can drive your career at IQVIA and choose the path that best defines your development and success. With exposure across diverse geographies, capabilities, and vast therapeutic and information and technology areas, you can seek opportunities to change and grow without boundaries.
We invite you to join IQVIA
IQVIA is a strong advocate of diversity and inclusion in the workplace. We believe that a work environment that embraces diversity will give us a competitive advantage in the global marketplace and enhance our success. We believe that an inclusive and respectful workplace culture fosters a sense of belonging among our employees, builds a stronger team, and allows individual employees the opportunity to maximise their personal potential.
IQVIA is a leading global provider of clinical research services, commercial insights and healthcare intelligence to the life sciences and healthcare industries. We create intelligent connections to accelerate the development and commercialization of innovative medical treatments to help improve patient outcomes and population health worldwide. Learn more at https://jobs.iqvia.com
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Data Scientist - Machine Learning employer: IQVIA Ltd. (GB80)
Contact Detail:
IQVIA Ltd. (GB80) Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist - Machine Learning
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with fellow data enthusiasts on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your machine learning projects, especially those relevant to healthcare. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Practice explaining complex concepts in simple terms, as you'll need to communicate effectively with both technical and non-technical stakeholders.
✨Tip Number 4
Don't forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, it shows you're genuinely interested in joining our team at IQVIA.
We think you need these skills to ace Data Scientist - Machine Learning
Some tips for your application 🫡
Show Off Your Skills: Make sure to highlight your experience with machine learning and data analysis in your application. We want to see how you've tackled complex problems and what tools you've used, so don’t hold back!
Tailor Your Application: Take a moment to customise your CV and cover letter for this role. Mention specific projects or experiences that align with the job description, especially those related to healthcare and life sciences.
Be Clear and Concise: When writing your application, keep it straightforward. Use clear language to explain your achievements and avoid jargon unless it's relevant. We appreciate good communication skills, so show us you can convey complex ideas simply!
Apply Through Our Website: We encourage you to submit your application through our website. It’s the best way to ensure your application gets into the right hands and shows us you're serious about joining our team!
How to prepare for a job interview at IQVIA Ltd. (GB80)
✨Know Your Machine Learning Stuff
Make sure you brush up on your machine learning techniques, especially gradient boosting classifiers like XGBoost and LightGBM. Be ready to discuss how you've applied these methods in real-world scenarios, particularly in healthcare or life sciences.
✨Show Off Your Data Skills
Prepare to demonstrate your proficiency in Python, R, and SQL. Have examples ready that showcase your experience with data science packages like sklearn and pandas. Being able to explain complex concepts in simple terms will impress both technical and non-technical interviewers.
✨Communicate Like a Pro
Since you'll be interacting with various stakeholders, practice explaining your analytical findings clearly and concisely. Think about how you can tailor your communication style to different audiences, ensuring everyone understands the insights you're providing.
✨Be Ready for Problem-Solving
Expect to tackle some real-world problems during the interview. Prepare by thinking through how you would approach complex challenges in the life sciences domain. Highlight your critical thinking skills and your ability to work collaboratively in cross-functional teams.