About ValGenesis
ValGenesis is a leading digital validation platform provider for life sciences companies. ValGenesis suite of products are used by 30 of the top 50 global pharmaceutical and biotech companies to achieve digital transformation, total compliance and manufacturing excellence/intelligence across their product lifecycle.
Learn more about working for ValGenesis, the de facto standard for paperless validation in Life Sciences: https://www.valgenesis.com/about
About the Role:
Technical Architecture & Hands-On Development
- Perform statistical analysis and apply advanced statistical modeling techniques
- Design, train, and optimize machine learning and deep learning models for various business use cases
- Deploy models into production environments and ensure reliable model serving and scalability
- Build and maintain robust GxP-compliant ML pipelines on cloud infrastructure (AWS/Azure/GCP) including data ingestion, preprocessing, training, and monitoring
- Evaluate model performance using appropriate metrics and continuously improve accuracy and efficiency
- Collaborate with cross-functional teams (engineering, product, and business stakeholders) to translate requirements into data-driven solutions
- Monitor deployed models for performance drift and retrain models as necessary
- Ensure best practices in model versioning, reproducibility, and documentation
- Conduct hands-on code reviews, architectural reviews, and model performance evaluations for all team deliverables.
People Leadership & Team Development
- Directly manage and mentor a team of 4–8 ML engineers, data scientists, and data engineers with defined technical goals and OKRs.
- Set individual development plans, run performance reviews, and build a culture of technical excellence, scientific rigor, and continuous learning.
- Recruit, interview, and hire top data science and ML engineering talent with strong domain experience in life sciences or regulated industries.
- Foster a collaborative environment where the team is empowered to propose, prototype, and ship novel ML solutions with speed and quality.
- Act as the technical escalation point for the team — unblocking architecture decisions, performance issues, and regulatory compliance questions.
Cross-Functional Collaboration
- Partner with the Product Manager (Data Science) to translate business and regulatory requirements into precise, implementable ML specifications.
- Collaborate with platform engineering on data infrastructure, API design, and integration of ML models into the ValGenesis SaaS platform.
- Work with the Quality and Compliance team to ensure all ML features are properly validated, documented, and audit-trail compliant under 21 CFR Part 11.
- Engage with strategic customers and key opinion leaders (KOLs) in the pharma industry to validate model approaches and gather technical feedback.
- Present technical architecture and model performance to executive leadership, customer CTOs, and regulatory affairs teams.
ML Operations & Governance
- Establish MLOps practices: model versioning, experiment tracking, automated retraining triggers, drift detection, and production monitoring.
- Define model governance standards for the GxP environment, including model qualification, change control, and periodic review procedures.
- Own the technical roadmap for the data science platform, balancing research innovation with production stability and regulatory compliance.
Education
- Degree in Statistics, Machine Learning, Computer Science, Biostatistics, Chemical Engineering, Pharmaceutical Sciences, or related quantitative field.
- Bachelor’s degree considered only with 8+ years of directly relevant hands-on experience.
Experience
- 5+ years of hands-on data science and ML engineering experience, with at least 3 years in a technical leadership or architect role.
- Proven track record of building and shipping production ML models at scale, not just research prototypes or POCs.
- 5+ years of experience in the pharmaceutical, biotech, or medical device industry in a technical role involving process data, quality analytics, or statistical modeling.
- Demonstrated hands-on experience building all model types listed in the Technical Skills Matrix above.
- Experience leading a team of 3+ data scientists or ML engineers with measurable outcomes.
PREFERRED QUALIFICATIONS
- Experience at a life sciences SaaS company or pharmaceutical analytics vendor
- Contributions to open-source ML libraries, statistical packages, or pharmaceutical data standards (CDISC, SDTM, ADaM).
- Certified in cloud ML platforms (AWS ML Specialty, Azure Data Scientist, GCP ML Engineer).
- Six Sigma Black Belt or ASQ CQE with a strong statistical application background.
We’re on a Mission
In 2005, we disrupted the life sciences industry by introducing the world’s first digital validation lifecycle management system. ValGenesis VLMS® revolutionized compliance-based corporate validation activities and has remained the industry standard.
Today, we continue to push the boundaries of innovation ― enhancing and expanding our portfolio beyond validation with an end-to-end digital transformation platform. We combine our purpose-built systems with world-class consulting services to help every facet of GxP meet evolving regulations and quality expectations.
The Team You’ll Join
Our customers’ success is our success. We keep the customer experience centered in our decisions, from product to marketing to sales to services to support. Life sciences companies exist to improve humanity’s quality of life, and we honor that mission.
We work together. We communicate openly, support each other without reservation, and never hesitate to wear multiple hats to get the job done.
We think big. Innovation is the heart of ValGenesis. That spirit drives product development as well as personal growth. We never stop aiming upward.
We’re in it to win it. We’re on a path to becoming the number one intelligent validation platform in the market, and we won’t settle for anything less than being a market leader.
How We Work
Our Chennai, Hyderabad and Bangalore offices are onsite, 5 days per week. We believe that in-person interaction and collaboration fosters creativity, and a sense of community, and is critical to our future success as a company.
ValGenesis is an equal-opportunity employer that makes employment decisions on the basis of merit. Our goal is to have the best-qualified people in every job. All qualified applicants will receive consideration for employment without regard to race, religion, sex, sexual orientation, gender identity, national origin, disability, or any other characteristics protected by local law.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. 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.
