Senior Principal Data Scientist

ZipRecruiter
Dalkeith
5 days ago
Applications closed

Related Jobs

View all jobs

Senior Data Science Director, London

Principal Oversight Statistician - Home or Office based, UK

Senior / Principal Recruitment Consultants - Data / Technology Perm & Interim

Senior/Principal Statistical Programmer - Submissions

Senior / Principal Biostatistician

Senior Operational Analyst Consultant

Job Description

This job is with Novartis, an inclusive employer and a member of myGwork – the largest global platform for the + business community. Please do not contact the recruiter directly.

Summary- Understand complex and critical business problems, formulate integrated analytical approaches to mine data sources, employ statistical methods and machine learning algorithms to contribute to solving unmet medical needs, discover actionable insights, and automate processes for reducing effort and time for repeated use. Manage the implementation and adherence to the overall data lifecycle of enterprise data from data acquisition or creation through enrichment, consumption, retention, and retirement, enabling the availability of useful, clean, and accurate data throughout its useful lifecycle. High agility to work across various business domains. Integrate business presentations, smart visualization tools, and contextual storytelling to translate findings back to business users with a clear impact. Independently manage budget, ensuring appropriate staffing and coordinating projects within the area. If managing a team: empowers the team and provides guidance and coaching, with initial guidance from more senior leaders supervised. This is usually their first people manager experience.

About the Role

Our Development Team is guided by our purpose: to reimagine medicine to improve and extend people's lives. To do this, we are optimizing and strengthening our processes and ways of working. We are investing in new technologies and building specific therapeutic area and platform depth and capabilities - all to bring our medicines to patients even faster. We are seeking key talent, like you, to join us and help give people with disease and their families a brighter future to look forward to. Apply today and welcome to where we thrive together!

The Role

As a Senior Principal Data Scientist in the Medical Affairs Advanced Quantitative Sciences group, you will be responsible for the discussion and implementation of data science methodologies applied to patient-level data (including various clinical, real-world, and biomarker data) across clinical development. You will combine your data science and AI skills and your scientific knowledge in biology or medicine to enrich drug development decisions in close collaboration with internal and external partners.

This role offers hybrid working, requiring 3 days per week or 12 days per month in our London Office.

Key Accountabilities:

  1. You will contribute to planning, execution, interpretation, validation, and communication of innovative exploratory analyses and algorithms, to facilitate internal decision making.
  2. You will provide technical expertise in data science and (predictive) machine learning/AI to identify opportunities for influencing internal decision making as well as discussions on white papers/regulatory policy.
  3. You will perform hands-on analysis of integrated data from clinical trials and the real world to generate fit-for-purpose evidence that is applied to decision making in drug development programs.

Your Experience

  1. Ph.D. in data science, biostatistics, or other quantitative field (or equivalent).
  2. More than 3 years experience in clinical drug development with extensive exposure to clinical trials.
  3. Strong knowledge and understanding of statistical methods such as time to event analysis, machine learning, meta-analysis, mixed effect modeling, longitudinal modeling, Bayesian methods, variable selection methods (e.g., lasso, elastic net, random forest), design of clinical trials.
  4. Strong programming skills in R and Python. Demonstrated knowledge of data visualization, exploratory analysis, and predictive modeling.
  5. Excellent interpersonal and communication skills (verbal and writing)
  6. Ability to develop and deliver clear and concise presentations for both internal and external meetings in key decision-making situations.

Why Novartis:Helping people with disease and their families takes more than innovative science. It takes a community of smart, passionate people like you. Collaborating, supporting, and inspiring each other. Combining to achieve breakthroughs that change patients' lives. Ready to create a brighter future together?

Commitment to Inclusion:Novartis is committed to building an outstanding, inclusive work environment and diverse teams representative of the patients and communities we serve.

Join our Novartis Network:Not the right Novartis role for you? Sign up to our talent community to stay connected and learn about suitable career opportunities as soon as they come up.

Benefits and Rewards:Read our handbook to learn about all the ways we'll help you thrive personally and professionally.

#LI-DNI

#J-18808-Ljbffr

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.

Tips for Staying Inspired: How Data Science Pros Fuel Creativity and Innovation

Data science sits at the dynamic intersection of statistics, computer science, and domain expertise, driving powerful innovations in industries ranging from healthcare to finance, and from retail to robotics. Yet, the daily reality for many data scientists can be a far cry from starry-eyed talk of AI and machine learning transformations. Instead, it often involves endless data wrangling, model tuning, and scrutiny over metrics. Maintaining a sense of creativity in this environment can be an uphill battle. So, how do successful data scientists continue to dream big and innovate, even when dealing with the nitty-gritty of data pipelines, debugging code, or explaining results to stakeholders? Below, we outline ten practical strategies to help data analysts, machine learning engineers, and research scientists stay inspired and push their ideas further. Whether you’re just starting out or looking to reinvigorate a long-standing career, these pointers can help you find fresh sparks of motivation.

Top 10 Data Science Career Myths Debunked: Key Facts for Aspiring Professionals

Data science has become one of the most sought-after fields in the tech world, promising attractive salaries, cutting-edge projects, and the opportunity to shape decision-making in virtually every industry. From e-commerce recommendation engines to AI-powered medical diagnostics, data scientists are the force behind innovations that drive productivity and improve people’s lives. Yet, despite the demand and glamour often associated with this discipline, data science is also shrouded in misconceptions. Some believe you need a PhD in mathematics or statistics; others assume data science is exclusively about machine learning or coding. At DataScience-Jobs.co.uk, we’ve encountered a wide array of myths that can discourage talented individuals or mislead those exploring a data science career. This article aims to bust the top 10 data science career myths—providing clarity on what data scientists actually do and illuminating the true diversity and inclusiveness of this exciting field. Whether you’re a recent graduate, a professional looking to pivot, or simply curious about data science, read on to discover the reality behind the myths.

Global vs. Local: Comparing the UK Data Science Job Market to International Landscapes

How to evaluate salaries, opportunities, and work culture in data science across the UK, the US, Europe, and Asia Data science has proven to be more than a passing trend; it is now a foundational pillar of modern decision-making in virtually every industry—from healthcare and finance to retail and entertainment. As the volume of data grows exponentially, organisations urgently need professionals who can transform raw information into actionable insights. This high demand has sparked a wave of new opportunities for data scientists worldwide. In this article, we’ll compare the UK data science job market to those in the United States, Europe, and Asia. We’ll explore hiring trends, salary benchmarks, and cultural nuances to help you decide whether to focus your career locally or consider opportunities overseas or in fully remote roles. Whether you’re a fresh graduate looking for your first data science position, an experienced data professional pivoting from analytics, or a software engineer eager to break into machine learning, understanding the global data science landscape can be a game-changer. By the end of this overview, you’ll be better equipped to navigate the expanding world of data science—knowing which skills and certifications matter most, how salaries differ between regions, and what to expect from distinct work cultures. Let’s dive in.