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- Tasks: Lead data science initiatives to solve critical medical challenges using advanced analytics and machine learning.
- Company: Join Novartis, a leader in innovative healthcare solutions dedicated to improving patient lives.
- Benefits: Enjoy hybrid work options, a collaborative culture, and opportunities for professional growth.
- Why this job: Make a real impact in drug development while working with cutting-edge technology and diverse teams.
- Qualifications: Ph.D. in a quantitative field and 3+ years in clinical drug development required.
- Other info: This role offers your first experience in people management, empowering and guiding your team.
The predicted salary is between 72000 - 108000 £ per year.
Join to apply for the Senior Principal Data Scientist role at Novartis Join to apply for the Senior Principal Data Scientist role at Novartis Summary The Multimodal Data and Analytics group is searching for a Principal Data Scientist. As the successful candidate, you will support the application of high-dimensional analyses of patient level data (including various -omics, phenomics, IHC, MRI, clinical and outcomes data) to mid to late development clinical programs in one or more indications. You will be part of interdisciplinary teams that analyze and interpret biomarker data to inform critical project decisions, regulatory submissions and directly influence drug development decisions with internal and external partners. Summary The Multimodal Data and Analytics group is searching for a Principal Data Scientist. As the successful candidate, you will support the application of high-dimensional analyses of patient level data (including various -omics, phenomics, IHC, MRI, clinical and outcomes data) to mid to late development clinical programs in one or more indications. You will be part of interdisciplinary teams that analyze and interpret biomarker data to inform critical project decisions, regulatory submissions and directly influence drug development decisions with internal and external partners. About The Role Principal Data Science, Multimodal Data & Analytics in Clinical Development 200+ compounds are supported by the quantitative drug developers at Novartis Development Analytics. We focus on transforming data from multiple (multimodal) sources – clinical, -omics, imaging – into analyses and insights that build the basis for making innovative drugs accessible for patients. We influence decision-making in cross-functional international teams from mid to late phase drug development. The Multimodal Data and Analytics group is searching for a Principal Data Scientist. As the successful candidate, you will support the application of high-dimensional analyses of patient level data (including various biomarker, clinical and outcomes data) to mid to late development clinical programs in one or more indications. You will be part of interdisciplinary teams that analyze and interpret biomarker data to inform critical project decisions and understand mechanisms of response/resistance to therapy. You will contribute to the design and execution of the biomarker strategy in those programs to inform drug development, and you will contribute to the strategy for addressing biomarker issues in late phase trials, regulatory submissions and directly influence drug development decisions with internal and external partners. The focus is less on method development or discovery, but on combining your domain knowledge of drug development, trials and biology with cutting-edge methodologies (ranging from survival models to machine learning) and technologies (imaging and multi-omics) to create tangible impact on clinical trials and patients. Key Requirements Ability to collaborate with cross-functional partners, provide quantitative, scientific and strategic input to support the execution of the integrated biomarker strategies in drug development that facilitate internal decision making, and support submissions of candidate drug. Ability to explain statistical concepts in an easily understandable way to non-statisticians and provide adequate statistical justifications and interpretation of analysis results for actions/decisions/statements, when required. Performing hands-on analysis of integrated clinical, outcomes and high-dimensional, patient-level biomarker data from clinical trials (genomics, transcriptomics, proteomics, flow cytometry etc.) to generate fit-for-purpose evidence that is applied for decision making in drug development programs. Essential Requirements Advanced degree in bioinformatics, statistics, data science or other quantitative discipline with extensive exposure to clinical trials and drug development. MS with 5+ years relevant work experience or PhD with 2+ years of relevant work experience in the pharma/biotech industry Good understanding of clinical study design principles and basic familiarity working with clinical data in a clinical trial (GxP) setting Strong knowledge and understanding of (multivariate implementations 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. Familiarity with statistical and analytical methods for genetics and -omics data analysis and working knowledge of high dimensional biomarker platforms (e.g., next generation sequencing, transcriptomics, proteomics, flow cytometry, etc.). Strong programming skills in R and Python. Demonstrated knowledge of data visualization, exploratory analysis and predictive modeling. Ability to leverage technical and scientific information from a variety of sources in order to effectively enable data analysis and the scientific interpretation of analysis results. Ability to develop and deliver clear and concise presentations for both internal and external meetings in key decision-making situations. Desirable Requirements Experience with modern data science methods and designing machine learning or other AI architectures for applications in healthcare Additional expertise in big data, web-based applications, good coding practice, source code management (Git, bitbucket) Exposure to and hands-on experience with various forms of RWE is a plus. 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? : https://www.novartis.com/about/strategy/people-and-culture Commitment To Diversity & Inclusion Novartis is committed to building an outstanding, inclusive work environment and diverse team’s 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: https://talentnetwork.novartis.com/network 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? https://www.novartis.com/about/strategy/people-and-culture 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: https://talentnetwork.novartis.com/network Benefits and Rewards: Read our handbook to learn about all the ways we’ll help you thrive personally and professionally: https://www.novartis.com/careers/benefits-rewards Seniority level Seniority level Mid-Senior level Employment type Employment type Full-time Job function Job function Engineering and Information Technology Industries Pharmaceutical Manufacturing Referrals increase your chances of interviewing at Novartis by 2x Get notified about new Senior Data Scientist jobs in London, England, United Kingdom . 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Senior Principal Data Scientist employer: Novartis
Contact Detail:
Novartis Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Principal Data Scientist
✨Tip Number 1
Familiarize yourself with the latest advancements in data science and machine learning, especially as they relate to clinical trials and drug development. This knowledge will help you engage in meaningful discussions during interviews and demonstrate your expertise.
✨Tip Number 2
Network with professionals in the pharmaceutical and biotech industries. Attend relevant conferences or webinars where you can meet people who work in data science roles similar to the one you're applying for. This can provide valuable insights and potentially lead to referrals.
✨Tip Number 3
Prepare to discuss specific projects where you've applied statistical methods and machine learning algorithms to real-world data. Be ready to explain your thought process, the challenges you faced, and how your contributions made an impact on the outcomes.
✨Tip Number 4
Showcase your ability to communicate complex data findings clearly and effectively. Practice presenting your analyses and results in a way that is accessible to non-technical stakeholders, as this skill is crucial for the role.
We think you need these skills to ace Senior Principal Data Scientist
Some tips for your application 🫡
Understand the Role: Before applying, make sure you fully understand the responsibilities and requirements of the Senior Principal Data Scientist position. Tailor your application to highlight your relevant experience in data science, clinical trials, and machine learning.
Highlight Relevant Experience: In your CV and cover letter, emphasize your Ph.D. and any relevant work experience in pre-clinical and clinical drug development. Be specific about your exposure to clinical trials and your knowledge of statistical methods and programming skills in R and Python.
Showcase Communication Skills: Since excellent interpersonal and communication skills are crucial for this role, provide examples in your application that demonstrate your ability to present complex data clearly and concisely to both technical and non-technical audiences.
Tailor Your Application: Customize your cover letter to reflect your understanding of Novartis' mission and values. Mention how your background aligns with their commitment to diversity and inclusion, and express your enthusiasm for contributing to innovative solutions in drug development.
How to prepare for a job interview at Novartis
✨Showcase Your Technical Expertise
Be prepared to discuss your experience with statistical methods and machine learning algorithms in detail. Highlight specific projects where you've applied these techniques, especially in the context of clinical trials or drug development.
✨Demonstrate Your Domain Knowledge
Make sure to convey your understanding of biology, pharmacology, or medicine. Discuss how this knowledge has influenced your data science work and decision-making processes in previous roles.
✨Prepare for Scenario-Based Questions
Expect questions that assess your problem-solving skills in real-world scenarios. Think about how you would approach complex business problems using data science methodologies and be ready to explain your thought process.
✨Communicate Clearly and Effectively
Since the role involves translating complex findings into actionable insights, practice explaining your work in a way that is accessible to non-technical stakeholders. Use examples from past experiences to illustrate your communication skills.
