Senior Data Scientist, Molecular Modeling and Drug Discovery (Specialist Senior) - SFL Scientific

Senior Data Scientist, Molecular Modeling and Drug Discovery (Specialist Senior) - SFL Scientific

SFL Scientific, a Deloitte Business practice brings together several key capabilities to architect integrated programs that transform our clients' businesses, including Business Strategy, Environmental, Social and Governance Strategy, Technology Strategy & Business Transformation, and AI & Data Strategy.

Professionals will serve as trusted advisors to our clients, working with them to make clear data-driven choices about where to play and how to win - ultimately driving growth and enterprise value.

We are hiring a Senior Data Scientist with technical and scientific expertise in AI-based drug discovery and molecular modeling to support our team in working with clients, organizing multi-project development, and enabling technical solution delivery.

Join a rapidly growing team of professionals working to build a world-class data science practice with a focus on solving complex R&D problems.

Recruiting for this role ends on 10 / 31 / 2024.

Work you'll do

As a Senior Data Scientist at SFL Scientific, a Deloitte Business, you will define data strategy, drive technical development, and help us create the next generation of tools, products, and AI services.

You will work closely with clients to understand their data sets, strategy, and operational requirements in order to drive exploratory analysis and design long-term solutions.

You will research, design, develop, and apply new AI / ML solutions for drug discovery and development, where you will lead the progress, validation, and interpretation of deep learning and GenAI-based pipelines for therapeutic modalities ranging from small molecules to biologics and nucleic acids.

Working with a team of interdisciplinary data scientists, engineers, architects, and consultants, our work includes novel areas such as cancer detection, drug discovery, protein design, chemical optimization, optimizing population health, and clinical trials.

This is a hands-on, highly collaborative Senior Data Scientist role working on modeling complex biological data and solving challenging chemical design problems to develop tools and platforms.

As a core member of the team, you will be focused on the implementation and validation of new methods and algorithms and work collaboratively with data scientists, engineers, and industry subject matter experts to aid in the research and advancement of novel protein, molecular, and discovery techniques.

Research and implement novel machine and deep learning approaches for Drug Discovery multimodal data, including various "omics" (transcriptomics, proteomics, etc.

biologics, small molecules, imaging, etc.

• Work as an individual contributor to prototype data pipelines and AI-based models using state-of-the-art algorithms relevant to R&D in the biological and chemical fields.
• Work closely with external organizations to understand their drug targets, data sets, strategy, and research requirements while driving exploratory analysis and designing long-term solutions.
• Take responsibility for relevant data identification, collection, QC, modeling, and validation to influence and impact pre-clinical and clinical programs for our clients.
• Guide clients with high autonomy in AI strategy and development, including understanding organizational needs, performing exploratory data analysis, building and validating models, and deploying models into production.
• Lead client initiatives to deliver AI / ML solutions, including providing thought leadership, long-term maintenance, and AI strategy objectives.
• Research and implement novel machine learning approaches, including advancing state-of-the-art training, solution design, network design, and hardware optimization
• Validate AI models and algorithms via code reviews, unit, and integration tests.
• Support prioritization of project performance and model development and ensure AI solutions are delivered to maximize business impact and new initiatives
• Collaborate with data engineers, data scientists, project managers, and business.
• Contribute to original research in the area of generative multimodal modeling, large language models (LLMs), diffusion models, probabilistic reasoning, and causality / causal representation learning applied to fundamental problems in life sciences.
• Build, train, and evaluate multimodal foundation models utilizing various modern GPUs and distributed training infrastructure.
• Work with a diverse range of multimodal and biological data types, including multi-omics data, cell / tissue images, human specimen / cohort data, bioassays, scientific literature, and more.

The Team

SFL Scientific, a Deloitte Business, is a data science professional services practice focused on strategy, technology, and solving business challenges with Artificial Intelligence (AI).

The team has a proven track record serving large, market-leading organizations in the private and public sectors, successfully delivering high-quality, novel, and complex projects, and offering deep domain and scientific capabilities.

Made up of experienced AI strategists, data scientists, and AI engineers, they serve as trusted advisors to executives, helping them understand and evaluate new and essential areas for AI investment and identify unique opportunities to transform their businesses.

Basic Qualifications :

• Master's or Ph.D. in a relevant STEM field (Data Science, Computer Science, Engineering, Physics, Mathematics, Biophysics, etc.)
• 3+ years of experience in AI / ML algorithm development and data analysis (NLP, time-series analysis, computer vision, LLMs, diffusion models)
• 3+ years of experience in traditional ML and deep learning techniques (CNNs, RNNs, LSTMs, GANs), model tuning, and validation of developed algorithms
• 3+ years of experience in core programming languages and data science packages (Python, Keras, Tensorflow, PyTorch, Pandas, Scikit-learn, Jupyter, etc.)
• 3+ years of experience with deployment and optimization - Kubernetes, Docker, NVIDIA TensorRT / Triton, RAPIDs, Kubeflow, MLflow, etc.
• 3+ years of experience with cloud deployment (AWS, Azure, GCP) preferred, such as building and scaling in AWS SageMaker or Azure ML Studio.
• Limited immigration sponsorship may be available
• Live within commuting distance of one of Deloitte's consulting offices
• Ability to travel 10%, on average, based on the work you do and the clients and industries / sectors you serve

Preferred Qualifications :

• Strong research interest in drug optimization and discovery, chemical properties prediction, computational chemistry, handling of "omics" pipelines, and cell imaging
• 3+ years of experience in R&D, AI modeling, scientific publications, and / or solution development within drug discovery or a related discipline
• Ability to interact at all levels of the client organization
• Excellent verbal and written communication skills and experience in a client-facing role is preferred

Information for applicants with a need for accommodation : https : / / www2.deloitte.com / us / en / pages / careers / articles / join-deloitte-assistance-for-disabled-applicants.html

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets;

experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled.

At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case.

A reasonable estimate of the current range is $131,175 to $218,625.

You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.

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