Associate Director, Data Science

Novartis
Novartis logo
Location
Cambridge (USA), Massachusetts
Job Type
Full-time
Posted
June 24, 2026
Views
7
Salary Range
$160k - $298k USD

Job Description

#LI-Hybrid Internal Title: Associate Director

Location: Cambridge, MANovartis is a leader in data science and model-informed drug development. We are seeking an experienced Data Science leader to advance data-driven drug discovery and development by integrating advanced analytics, machine learning, and mechanistic modelling approaches.In this role, you will partner with Pharmacokinetic Sciences (PKS) Modeling & Simulation (M&S), Translational Medicine, and multidisciplinary project teams to transform large-scale experimental datasets into actionable insights.

You will develop and apply hybrid approaches that combine machine learning with mechanistic modelling (e.g., PK/PD, QSP) to support decision-making from discovery through clinical development.You will contribute to departmental strategy, drive innovation in AI-augmented modelling approaches, and ensure the proactive use of data science and in silico methods to guide compound progression, prioritization, and clinical decision-making.This role reports to the Head of Data Science in the PKS M&S team within Translational Medicine in Biomedical Research.Key

responsibilities:Shape and advance AI-driven MIDD by integrating mechanistic modelling and machine learning to bridge biology and clinical outcomes.Design and implement hybrid modelling pipelines where mechanistic simulations generate features for machine learning models.Translate model-derived biomarkers and mechanistic states into clinically relevant predictions and decision-support tools.Drive scientifically grounded AI approaches that enhance mechanistic understanding, ensuring rigor, interpretability, and robustness.Develop scalable, reproducible workflows integrating data science, mechanistic modelling, and in-house tools.Define and implement project-specific in silico modelling and data strategies aligned with key decision questions.Apply and advance currently available data mining and advanced analytics to link molecular structure, ADME properties, and pharmacological outcomes across modalities.Drive adoption and effective use of in silico models, tools, and data to accelerate decision-making.Collaborate with PKS, Translational Medicine, and Data & Digital teams to integrate diverse datasets (preclinical, clinical, external).Contribute to translational programs across disease areas and communicate modelling insights to influence decision-making.Stay current with advances in AI/ML and their application to ADME, PK/PD, and drug discovery and development, and proactively evaluate and bring appropriate innovation into practice to improve efficiency and scientific impact.Essential requirementsAdvanced degree in life sciences or quantitative discipline (e.g., data science, computational biology, pharmacometrics, bioinformatics, computational chemistry, biomedical engineering or related field).PhD with 5+ years or MSc with 8+ years of relevant experience in drug discovery or development.Strong expertise in machine learning, statistics, and data science methods.Demonstrated experience applying reproducible data science approaches to drug discovery or development.Experience combining mechanistic modelling and data-driven approaches is strongly preferred.Strong understanding of ADME, PK/PD, and/or translational modelling concepts.Proficiency in Python and/or R, including software development best practices (version control, testing, documentation).Experience with machine learning libraries such as scikit-learn, PyTorch, or Keras.Strong data visualization and exploratory data analysis skills.Ability to translate complex analytical concepts into clear, actionable insights.Strong collaboration and communication skills across multidisciplinary teams.Fluency in English (oral and written).This is a hybrid role that requires a balance of in-person and virtual working, with an average of 12 days a month on site in Cambridge, MA.The salary for this position is expected to range between $160,300 and $297,700 per year.The final salary offered is determined based on factors like, but not limited to, relevant skills and experience, and upon joining Novartis will be reviewed periodically.

Novartis may change the published salary range based on company and market factors.Your compensation will include a performance-based cash incentive and, depending on the level of the role, eligibility to be considered for annual equity awards.

US-based eligible employees will receive a comprehensive benefits package that includes health, life and disability benefits, a 401(k) with company contribution and match, and a variety of other benefits.

#LI-Hybrid Internal Title: Associate Director

Location: Cambridge, MANovartis is a leader in data science and model-informed drug development. We are seeking an experienced Data Science leader to advance data-driven drug discovery and development by integrating advanced analytics, machine learning, and mechanistic modelling approaches.In this role, you will partner with Pharmacokinetic Sciences (PKS) Modeling & Simulation (M&S), Translational Medicine, and multidisciplinary project teams to transform large-scale experimental datasets into actionable insights.

You will develop and apply hybrid approaches that combine machine learning with mechanistic modelling (e.g., PK/PD, QSP) to support decision-making from discovery through clinical development.You will contribute to departmental strategy, drive innovation in AI-augmented modelling approaches, and ensure the proactive use of data science and in silico methods to guide compound progression, prioritization, and clinical decision-making.This role reports to the Head of Data Science in the PKS M&S team within Translational Medicine in Biomedical Research.Key

responsibilities:Shape and advance AI-driven MIDD by integrating mechanistic modelling and machine learning to bridge biology and clinical outcomes.Design and implement hybrid modelling pipelines where mechanistic simulations generate features for machine learning models.Translate model-derived biomarkers and mechanistic states into clinically relevant predictions and decision-support tools.Drive scientifically grounded AI approaches that enhance mechanistic understanding, ensuring rigor, interpretability, and robustness.Develop scalable, reproducible workflows integrating data science, mechanistic modelling, and in-house tools.Define and implement project-specific in silico modelling and data strategies aligned with key decision questions.Apply and advance currently available data mining and advanced analytics to link molecular structure, ADME properties, and pharmacological outcomes across modalities.Drive adoption and effective use of in silico models, tools, and data to accelerate decision-making.Collaborate with PKS, Translational Medicine, and Data & Digital teams to integrate diverse datasets (preclinical, clinical, external).Contribute to translational programs across disease areas and communicate modelling insights to influence decision-making.Stay current with advances in AI/ML and their application to ADME, PK/PD, and drug discovery and development, and proactively evaluate and bring appropriate innovation into practice to improve efficiency and scientific impact.Essential requirementsAdvanced degree in life sciences or quantitative discipline (e.g., data science, computational biology, pharmacometrics, bioinformatics, computational chemistry, biomedical engineering or related field).PhD with 5+ years or MSc with 8+ years of relevant experience in drug discovery or development.Strong expertise in machine learning, statistics, and data science methods.Demonstrated experience applying reproducible data science approaches to drug discovery or development.Experience combining mechanistic modelling and data-driven approaches is strongly preferred.Strong understanding of ADME, PK/PD, and/or translational modelling concepts.Proficiency in Python and/or R, including software development best practices (version control, testing, documentation).Experience with machine learning libraries such as scikit-learn, PyTorch, or Keras.Strong data visualization and exploratory data analysis skills.Ability to translate complex analytical concepts into clear, actionable insights.Strong collaboration and communication skills across multidisciplinary teams.Fluency in English (oral and written).This is a hybrid role that requires a balance of in-person and virtual working, with an average of 12 days a month on site in Cambridge, MA.The salary for this position is expected to range between $160,300 and $297,700 per year.The final salary offered is determined based on factors like, but not limited to, relevant skills and experience, and upon joining Novartis will be reviewed periodically.

Novartis may change the published salary range based on company and market factors.Your compensation will include a performance-based cash incentive and, depending on the level of the role, eligibility to be considered for annual equity awards.

US-based eligible employees will receive a comprehensive benefits package that includes health, life and disability benefits, a 401(k) with company contribution and match, and a variety of other benefits.

In addition, employees are eligible for a generous time off package including vacation, personal days, holidays and other leaves.To learn more about the culture, rewards and benefits we offer our people click here.

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Frequently Asked Questions

Where is the job located, and is it remote, hybrid, or on-site?
The position is based in Cambridge, Massachusetts, USA. It is a hybrid role that requires an average of 12 days a month on-site, balancing in-person and virtual work.
What are the required qualifications and experience for this role?
You need an advanced degree in a life sciences or quantitative discipline. This must include either a PhD with 5+ years of experience or an MSc with 8+ years of experience in drug discovery or development, alongside strong expertise in machine learning, statistics, and Python or R.
What are the key responsibilities of the Associate Director, Data Science?
You will integrate mechanistic modelling and machine learning to advance AI-driven drug development. Key tasks include designing hybrid modelling pipelines, translating model-derived biomarkers into clinical predictions, developing scalable workflows, and collaborating with multidisciplinary teams to guide compound progression and decision-making.
What is the salary range for this position?
The expected annual salary range is $160,300 to $297,700. The final offer is determined by factors such as relevant skills and experience.
What benefits and compensation packages are offered?
Compensation includes a performance-based cash incentive and potential eligibility for annual equity awards. Eligible US employees receive health, life, and disability benefits, a 401(k) with company match, and a generous time-off package including vacation, personal days, holidays, and other leaves.
Who will I report to in this role?
You will report directly to the Head of Data Science in the Pharmacokinetic Sciences (PKS) Modeling & Simulation (M&S) team within Translational Medicine in Biomedical Research.

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Job Information

Source: manual
AI Relevance: 85/100 (Highly relevant)
Remote Type: onsite
Allowed Locations: Worldwide
Skills & Tags:
u175 (fcrs = us175) novartis institutes for biomedical research,inc. machine learning bioinformatics computational biology drug discovery data science clinical

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