Engineer the Quantum RevolutionYour expertise can help us shape the future of quantum computing at Oxford Ionics.

View Open Roles

Senior Expert Data Scientist (Oncology) – Data42

Healthcare Businesswomen’s Association
Cambridge
2 days ago
Create job alert

Job Description Summary

Location: Cambridge, US Full time, Onsite

At data42, a division of Biomedical Research, our vision is to empower and inspire Novartis’ research and development community in harnessing inter-connected multimodal internal and external data in a securely governed platform. We strive to accelerate additional research across a continuum of research, Clinical development and medical to unlock insights leading to the discovery and development of new medicines for patients.

Data42 science delivery team is currently seeking a highly skilled individual to join our team as a Senior Data Science Expert. As an essential part of the team, you will collaborate with scientists in various disease and functional areas across the organization to advance research and drug development, specifically in our oncology programs.

With a focus on addressing unmet medical needs in oncology, your responsibilities will involve collaborating with other data42 scientists to design a comprehensive platform for our users and stakeholders to explore while ensuring proper governance.

If you are passionate about making a significant impact in medical research and are eager to join a dynamic and collaborative team, we encourage you to apply. There are numerous diseases with urgent medical needs, and our goal is to address these challenges and create a lasting impact on global healthcare.

Job Description

Major accountabilities:

  • Leading projects and effectively communicating with stakeholders and collaborators.
  • Actively participating in the design and development of clinical pipeline and customization of pooling trial data as needed to address important scientific questions, such as indication expansion.
  • Independently designing, using, and improving bioinformatics tools and models that are specifically designed for integrating different types of data, enabling the exploration of various biological layers.
  • Acting as a connector between valuable data resources and project teams, enhancing the generation of hypotheses by sharing insights derived from or applied to late-stage pipeline data.

Essential Requirements:

  • Preferably PhD in quantitative field such as computer science, data science, mathematics, statistics, or physics. Experience working on problems in the life sciences is a plus.
  • At least 2 years of professional experience in the pharmaceutical or clinical sector.
  • Experience in at least one of the following: - Using biostatistics methods for inference and hypothesis testing, such as linear and logistic regression or Cox proportional hazard models, and leveraging clinical data for secondary analysis. - Track record of applying AI / deep learning to scientific data. - Experience in using machine learning models to predict clinical endpoints using multimodal data.
  • Experience with Python and R scientific stacks, track record of building custom scientific software using best practices (version control, testing, documentation).
  • Ability to work as part of an intercultural and interdisciplinary team, including biologists, chemists, and data scientists. Strong communication skills in verbal, written, and virtual formats.

Nice to have:

  • Hands-on expertise and a proven track record in utilizing patient/clinical data to generate actionable hypotheses.
  • Knowledge of computer programing language SPARK and Experience in using Foundry for data analysis.
  • Published research in machine learning conferences such as ICML, ICLR, NeurIPS, or comparable venues

EEO Statement:

The Novartis Group of Companies are Equal Opportunity Employers. We do not discriminate in recruitment, hiring, training, promotion or other employment practices for reasons of race, color, religion, sex, national origin, age, sexual orientation, gender identity or expression, marital or veteran status, disability, or any other legally protected status.

Accessibility and reasonable accommodations

The Novartis Group of Companies are committed to working with and providing reasonable accommodation to individuals with disabilities. If, because of a medical condition or disability, you need a reasonable accommodation for any part of the application process, or to perform the essential functions of a position, please send an e-mail to or call +1(877)395-2339 and let us know the nature of your request and your contact information. Please include the job requisition number in your message.

Salary Range

$119,700.00 - $222,300.00

Skills Desired

Apache Hadoop, Applied Mathematics, Big Data, Curiosity, Data Governance, Data Literacy, Data Management, Data Quality, Data Science, Data Strategy, Data Visualization, Deep Learning, Machine Learning (Ml), Machine Learning Algorithms, Master Data Management, Proteomics, Python (Programming Language), R (Programming Language), Statistical Modeling
#J-18808-Ljbffr

Related Jobs

View all jobs

Senior Data Scientist

Staff Data Scientist

Senior Data Scientist - Retail Price Optimisation - Motor

4953-E - Programme Lead - Data Science (Greenwich Online)

Senior Data Scientist

Senior Data Scientist

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Pre-Employment Checks for Machine Learning Jobs: DBS, References & Right-to-Work and more Explained

Pre-employment screening in machine learning reflects the discipline's unique position at the intersection of artificial intelligence research, algorithmic decision-making, and transformative business automation. Machine learning professionals often have privileged access to proprietary datasets, cutting-edge algorithms, and strategic AI systems that form the foundation of organizational competitive advantage and automated decision-making capabilities. The machine learning industry operates within complex regulatory frameworks spanning AI governance directives, algorithmic accountability requirements, and emerging ML ethics regulations. Machine learning specialists must demonstrate not only technical competence in model development and deployment but also deep understanding of algorithmic fairness, AI safety principles, and the societal implications of automated decision-making at scale. Modern machine learning roles frequently involve developing systems that impact hiring decisions, financial services, healthcare diagnostics, and autonomous operations across multiple regulatory jurisdictions and ethical frameworks simultaneously. The combination of algorithmic influence, predictive capabilities, and automated decision-making authority makes thorough candidate verification essential for maintaining compliance, fairness, and public trust in AI-powered systems.

Why Now Is the Perfect Time to Launch Your Career in Machine Learning: The UK's Intelligence Revolution

The United Kingdom stands at the epicentre of a machine learning revolution that's fundamentally transforming how we solve problems, deliver services, and unlock insights from data at unprecedented scale. From the AI-powered diagnostic systems revolutionising healthcare in Manchester to the algorithmic trading platforms driving London's financial markets, Britain's embrace of intelligent systems has created an extraordinary demand for skilled machine learning professionals that dramatically exceeds the current talent supply. If you've been seeking a career at the forefront of technological innovation or looking to position yourself in one of the most impactful sectors of the digital economy, machine learning represents an exceptional opportunity. The convergence of abundant data availability, computational power accessibility, advanced algorithmic development, and enterprise AI adoption has created perfect conditions for machine learning career success.

Automate Your Machine Learning Jobs Search: Using ChatGPT, RSS & Alerts to Save Hours Each Week

ML jobs are everywhere—product companies, labs, consultancies, fintech, healthtech, robotics—often hidden in ATS portals or duplicated across boards. The fastest way to stay on top of them isn’t more scrolling; it’s automation. With keyword-rich alerts, RSS feeds, and a reusable ChatGPT workflow, you can bring relevant roles to you, triage them in minutes, and tailor strong applications without burning your evenings. This is a copy-paste playbook for www.machinelearningjobs.co.uk readers. It’s UK-centric, practical, and designed to save you hours each week. What You’ll Have Working In 30 Minutes A role & keyword map spanning LLM/NLP, Vision, Core ML, Recommenders, MLOps/Platform, Research/Applied Science, and Edge/Inference optimisation. Shareable Boolean searches you can paste into Google & job boards to cut noise. Always-on alerts & RSS feeds delivering fresh roles to your inbox/reader. A ChatGPT “ML Job Scout” prompt that deduplicates, scores fit, and outputs tailored actions. A lightweight pipeline tracker so deadlines and follow-ups never slip.