[High Salary] Associate Director Data Science...

Novartis Farmacéutica
London
1 day ago
Create job alert

-Understands complex and critical business problems
from a variety of stakeholders and business functions, formulate
integrated analytical approach to mine data sources, employ
statistical methods and machine learning algorithms to contribute
solving unmet medical needs, discover actionable insights and
automate process for reducing effort and time for repeated use. To
manage the definition, 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 be able 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
set strategy, manage budget, ensuring appropriate staffing and
coordinating projects within the area supervised. If managing a
team: empowers the team and provides guidance and coaching, with
limited guidance from more senior managers. 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 an Associate
Director Data Science 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 6 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? Learn more.
Commitment to Diversity & 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: Join here.
GB16 (FCRS = GB016) Novartis Pharmaceuticals UK Ltd. Novartis is
committed to building an outstanding, inclusive work environment
and diverse teams' representative of the patients and communities
we serve. #J-18808-Ljbffr

Related Jobs

View all jobs

Associate Director, Data Science and Innovation

Associate Director, Data Science and Innovation (Basé à London)

Technical Mobilisation Coordinator

Trainee Data Analyst (Career Accelerator with Employment Guarantee)

Trainee Data Analyst (Career Accelerator with Employment Guarantee)

Trainee Data Analyst (Career Accelerator with Employment Guarantee)

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.

Quantum-Enhanced AI in Data Science: Embracing the Next Frontier

Data science has undergone a staggering transformation in the past decade, evolving from a niche academic discipline into a linchpin of modern industry. Across every sector—finance, healthcare, retail, manufacturing—data scientists have become indispensable, leveraging statistical methods and machine learning to turn raw information into actionable insights. Yet as datasets grow ever larger and machine learning models become more computationally expensive, there are genuine questions about how far current methods can be pushed. Enter quantum computing, a nascent but promising technology grounded in the counterintuitive principles of quantum mechanics. Often dismissed just a few years ago as purely experimental, quantum computing is quickly gaining traction as prototypes evolve into cloud-accessible machines. When paired with artificial intelligence—particularly in the realm of data science—the results could be game-changing. From faster model training and complex optimisation to entirely new forms of data analysis, quantum-enhanced AI stands poised to disrupt established practices and create new opportunities. In this article, we will: Explore how data science has reached its current limits in certain areas, and why classical hardware might no longer suffice. Provide an accessible overview of quantum computing concepts and how they differ from classical systems. Examine the potential of quantum-enhanced AI to solve key data science challenges, from data wrangling to advanced machine learning. Highlight real-world applications, emerging job roles, and the skills you need to thrive in this new landscape. Offer actionable steps for data professionals eager to stay ahead of the curve in a rapidly evolving field. Whether you’re a practising data scientist, a student weighing up your future specialisations, or an executive curious about the next technological leap, read on. The quantum era may be closer than you think, and it promises to radically transform the very fabric of data science.

Data Science Jobs at Newly Funded UK Start-ups: Q3 2025 Investment Tracker

Data science has become an indispensable cornerstone of modern business, driving decisions across finance, healthcare, e-commerce, manufacturing, and beyond. As organisations scramble to capitalise on the insights their data can offer, data scientists and machine learning (ML) experts find themselves in ever-higher demand. In the UK, which has cultivated a robust ecosystem of tech innovation and academic excellence, data-driven start-ups continue to blossom—fuelled by venture capital, government grants, and a vibrant talent pool. In this Q3 2025 Investment Tracker, we delve into the newly funded UK start-ups making waves in data science. Beyond celebrating their funding milestones, we’ll explore the job opportunities these investments have created for aspiring and seasoned data scientists alike. Whether you’re interested in advanced analytics, NLP (Natural Language Processing), computer vision, or MLOps, these start-ups might just offer the career leap you’ve been waiting for.

Portfolio Projects That Get You Hired for Data Science Jobs (With Real GitHub Examples)

Data science is at the forefront of innovation, enabling organisations to turn vast amounts of data into actionable insights. Whether it’s building predictive models, performing exploratory analyses, or designing end-to-end machine learning solutions, data scientists are in high demand across every sector. But how can you stand out in a crowded job market? Alongside a solid CV, a well-curated data science portfolio often makes the difference between getting an interview and getting overlooked. In this comprehensive guide, we’ll explore: Why a data science portfolio is essential for job seekers. Selecting projects that align with your target data science roles. Real GitHub examples showcasing best practices. Actionable project ideas you can build right now. Best ways to present your projects and ensure recruiters can find them easily. By the end, you’ll be equipped to craft a compelling portfolio that proves your skills in a tangible way. And when you’re ready for your next career move, remember to upload your CV on DataScience-Jobs.co.uk so that your newly showcased work can be discovered by employers looking for exactly what you have to offer.