AI Solutions Lead

Johnson & Johnson Co.; Penjerla; Hybrid; INR 4,000,000 - 7,000,000; Full time

Job summary

Johnson & Johnson's APAC Business Technology Team seeks an AI Solution Lead to design, build, and deploy scalable AI and GenAI solutions. The role collaborates with Business, Commercial Excellence, Marketing, and Technology to translate challenges into practical AI-enabled outcomes.

The candidate should combine strong data science foundations with hands-on GenAI experience, owning the full lifecycle from problem framing to deployment and value realization while upholding Responsible AI and

Qualifications

• Strong foundation in statistics, probability, hypothesis testing, and experimental design.

Responsibilities

• Translate business challenges into analytical approaches, ML models, and AI-enabled solutions.
• Analyze structured and unstructured data to identify insights and opportunities.
• Develop, validate, and deploy predictive, classification, segmentation, forecasting, and optimization models.
• Apply statistical analysis and experimentation to improve outcomes and decision-making.
• Design experiments (A/B tests, pilot studies) to measure impact of interventions and AI solutions.
• Define success metrics and measure impact via KPIs across business, operations, and adoption.
• Communicate findings and recommendations to business and technical stakeholders.

Skills

Statistics

A/B testing

Data Visualization

Python

SQL

PySpark

Experiment design

Communication

Leadership

Problem solving

Education

Advanced degree in Data Science/Statistics

PhD/ MSc in a quantitative field

Tools

Databricks

Azure/AWS

Azure ML/AWS Bedrock

Python (pandas)

Job description

At Johnson & Johnson, we believe health is everything. Our strength in healthcare innovation empowers us to build a world where complex diseases are prevented, treated, and cured, where treatments are smarter and less invasive, and solutions are personal. Through our expertise in Innovative Medicine and MedTech, we are uniquely positioned to innovate across the full spectrum of healthcare solutions today to deliver the breakthroughs of tomorrow, and profoundly impact health for humanity. Learn more at jnj.com.

As guided by Our Credo, Johnson & Johnson is responsible to our employees who work with us throughout the world. We provide an inclusive work environment where each person is considered as an individual. At Johnson & Johnson, we respect the diversity and dignity of our employees and recognize their merit.

Job Function:

Data Analytics & Computational Sciences

Job Sub Function:

Data Science

Job Category:

People Leader

All Job Posting Locations:

PENJERLA, Telangana, India

Job Description:

Overview

The APAC Business Technology Team within Johnson & Johnson Innovative Medicine is seeking an AI Solution Lead to design, build, and deploy scalable AI, Generative AI, machine learning, and advanced analytics solutions that improve commercial effectiveness, customer engagement, and business decision-making.

This role will partner closely with Business, Commercial Excellence, Marketing, and Technology teams to translate business challenges into practical AI-enabled solutions. The ideal candidate combines strong foundations in data science, machine learning, statistics, experimentation, and advanced analytics with hands‑on experience applying Generative AI technologies to solve real‑world business problems.

The role is expected to contribute across the full solution lifecycle, from business problem framing and data analysis through model development, GenAI solution design, deployment, adoption, and value realization, while ensuring responsible AI, security, compliance, and enterprise technology standards are met.

Tasks / Duties / Responsibilities

Data Science & Advanced Analytics

• Translate business challenges into analytical approaches, machine learning models, and AI‑enabled solutions.
• Explore, transform, and analyze structured and unstructured data to identify insights and business opportunities.
• Develop, validate, and deploy predictive, classification, segmentation, recommendation, forecasting, optimization, and causal models.
• Apply statistical analysis, hypothesis testing, machine learning, and experimentation techniques to improve business outcomes and decision‑making.
• Design and evaluate experiments, including A/B tests and pilot studies, to measure the effectiveness and impact of business interventions, digital products, and AI solutions.
• Define success metrics and measure solution impact through business, operational, and adoption KPIs.
• Communicate analytical findings, model outputs, and recommendations to both business and technical stakeholders.

AI Solution Delivery

• Design, build, and support Generative AI solutions using approaches such as prompt engineering, agentic workflows, tool orchestration, model evaluation, and monitoring.
• Evaluate and apply appropriate AI, machine learning, and Generative AI techniques based on business needs and value potential.
• Develop scalable AI solutions that are reliable, secure, and aligned with enterprise standards.
• Embed Responsible AI, privacy, security, and compliance principles throughout the solution lifecycle.
• Evaluate emerging AI technologies, tools, and methodologies and recommend practical adoption opportunities.

Business Partnership & Product Collaboration

• Partner with business stakeholders to understand objectives and translate them into analytical and technical requirements.
• Define clear success metrics and expected business outcomes for AI solutions.
• Communicate solution options, trade‑offs, risks, and recommendations clearly to business and technology audiences.
• Collaborate with product owners, data engineers, architects, and vendors to deliver end‑to‑end AI solutions.
• Support delivery of AI products and capabilities that drive measurable business value.

Research & Innovation

• Stay current with advancements in Generative AI, machine learning, advanced analytics, statistics, experimentation methodologies, and cloud technologies.
• Evaluate emerging tools, techniques, and methodologies to enhance AI capabilities and business impact.
• Lead targeted experimentation and proof‑of‑concepts, scaling successful ideas into production‑ready solutions.
• Promote adoption of innovative AI and analytics capabilities across the organization.

Required Years of Related Experience

• 5+ years of experience in Data Science, Machine Learning, Advanced Analytics, AI solution development, or related disciplines.
• 2+ years of experience designing and deploying AI/ML or Generative AI solutions.
• Experience delivering solutions across the end‑to‑end lifecycle, from business problem framing and data analysis through deployment and value realization.

Required Knowledge, Skills and Abilities

• Strong foundation in statistics, probability, hypothesis testing, experimental design, A/B testing, machine learning, predictive modelling, feature engineering, and model evaluation.
• Experience applying analytical techniques to solve commercial, marketing, customer engagement, forecasting, segmentation, targeting, optimization, or business performance challenges.
• Experience designing and evaluating experiments to measure business impact, user behavior, product effectiveness, marketing effectiveness, or customer engagement outcomes.
• Hands‑on experience designing and deploying Generative AI solutions using prompt engineering, agentic workflows, tool orchestration, model evaluation, and monitoring approaches.
• Experience building, evaluating, and deploying machine learning and AI solutions in business environments.
• Practical experience with cloud and data platforms such as Databricks, Azure, AWS, Azure ML, or AWS Bedrock.
• Strong programming skills in Python, SQL, and PySpark.
• Experience integrating AI solutions with APIs, enterprise data platforms, and business applications.
• Understanding of Responsible AI, privacy, security, and compliance considerations for AI solutions.
• Ability to translate ambiguous business problems into structured analytical and technical solutions.
• Strong communication skills with the ability to explain complex AI concepts to business and technology stakeholders.
• Ability to work effectively in a matrixed, cross‑functional environment and manage multiple priorities.
• Strong ownership mindset, problem‑solving ability, and willingness to operate hands‑on.

Preferred Qualifications

• Experience applying AI, machine learning, or advanced analytics within healthcare, pharmaceuticals, FMCG, retail, e‑commerce, or related industries.
• Experience supporting customer engagement, segmentation, targeting, personalization, forecasting, marketing effectiveness, commercial effectiveness, sales force effectiveness, next‑best‑action, or customer insights use cases.
• Education or strong foundations in Statistics, Machine Learning, Data Science, Advanced Analytics, Econometrics, Operations Research, Applied Mathematics, or related quantitative disciplines.

Required Skills:

Preferred Skills:

Advanced Analytics, Compliance Management, Critical Thinking, Data Analysis, Data Privacy Standards, Data Quality, Data Reporting, Data Savvy, Data Science, Data Visualization, Developing Others, Digital Fluency, Give Feedback, Inclusive Leadership, Leadership, Proactive Behavior, Resource Allocation, Strategic Thinking, Team Management