Lead Data Scientist (US Healthcare)

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Lead Data Scientist based in India.
This role offers the opportunity to lead data science strategy for innovative B2B SaaS products serving the healthcare and CPG industries.
You will work at the intersection of business, mathematics, technology, and advanced analytics to solve complex problems and drive measurable business impact.
The position combines hands-on technical leadership with strategic ownership of data science initiatives aligned with the product roadmap.
You will apply statistical modeling, machine learning, deep learning, and explainable AI techniques to turn complex data into actionable insights.
As the team grows, you will hire, coach, and develop talented data scientists while fostering a culture of creativity, experimentation, and execution.
You will collaborate closely with engineers and other technical experts to transform advanced models into scalable product capabilities.
The role also provides opportunities to contribute to industry thought leadership through research, publications, conferences, and innovative analytical approaches.
Accountabilities
The Lead Data Scientist will own the data science strategy and help translate advanced analytics into scalable product capabilities, while leading a growing team of data science professionals.
Define and execute the data science strategy in alignment with product goals and business priorities.
Lead data science initiatives that support the development and evolution of AI/ML-powered B2B SaaS products.
Solve complex business challenges by combining traditional statistical and mathematical modeling with modern AI, machine learning, and deep learning techniques.
Develop and apply advanced analytical approaches to generate meaningful insights from broad and complex datasets.
Transform complex or black-box AI models into more transparent and interpretable solutions using explainable AI techniques.
Work hands-on with data scientists, software engineers, and other technical teams to turn analytical concepts into scalable product solutions.
Promote a culture of creative thinking, experimentation, ownership, and practical problem-solving across the data science organization.
Hire, mentor, guide, and coach Data Science team members while developing the capabilities required to support rapid organizational growth.
Establish effective approaches, standards, and practices for data science, modeling, experimentation, and delivery.
Help democratize advanced analytics by enabling business users to leverage data and analytical insights to address complex business challenges.
Contribute to thought leadership through whitepapers, articles, conferences, and other industry-facing initiatives.
Stay current with emerging AI/ML methodologies and identify opportunities to incorporate relevant innovations into products and solutions.
Requirements
The ideal candidate combines strong hands-on data science expertise with the ability to lead teams, structure complex problems, and translate advanced analytical techniques into tangible business outcomes.
Master’s degree in Machine Learning, Mathematics, Computer Science, Statistics, Economics, or a related quantitative field.
6+ years of hands-on experience developing and applying data-driven solutions in a corporate or consulting environment.
Experience working in or with CPG, Retail, Healthcare, or other data-intensive industries is preferred.
Strong understanding of statistical and machine learning techniques, including regression, boosting, segmentation, Marketing Mix Modeling (MMM), and deep learning.
Demonstrated ability to solve complex data science problems using both traditional analytical methods and advanced AI/ML/DL techniques.
Hands-on experience with R, Python, Spark, TensorFlow, Caffe, and PyTorch.
Experience working with big data platforms and technologies such as Apache Spark and Hadoop.
Strong knowledge of data engineering, data modeling, algorithms, and modern data science practices.
Ability to translate complex analytical concepts into practical business solutions and measurable outcomes.
Strong problem-solving skills with the ability to structure, prioritize, and execute analytical approaches based on potential business impact.
Intellectual curiosity and a continuous interest in emerging technologies and analytical methodologies.
Demonstrated ability to lead, motivate, and develop high-performing data science teams.
A hands-on, execution-oriented mindset with the ability to move from strategy and ideas to implementation.
Strong communication and collaboration skills when working with technical and business stakeholders.
Benefits
Remote work opportunity based in Karnataka, India.
Opportunity to lead data science strategy for AI/ML-powered B2B SaaS products.
Exposure to complex business challenges across the healthcare and CPG industries.
Strong combination of strategic leadership and hands-on technical work.
Opportunity to build and scale a Data Science team as the organization grows.
Collaboration with experienced data scientists, engineers, and multidisciplinary teams.
Opportunity to work with advanced AI, machine learning, deep learning, and explainable AI technologies.
Opportunities to contribute to thought leadership through whitepapers, industry articles, and conferences.
High level of ownership and influence over data science initiatives and product development.
How Jobgether Works
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
We appreciate your interest and wish you the best!
Why Apply Through Jobgether?
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We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

Work arrangement
No