Immediate Joiner | Consultant / Senior Consultant / Project Manager – Advanced Analytics & AI

PharmaACE; Pune District; On-site; INR 900,000 - 1,300,000; Full time

Job summary

PharmaACE is seeking a Consultant/Senior Consultant/Project Manager for Advanced Analytics & AI in Pune, India. Immediate joiner. You will own patient journey analytics, develop ML/NLP models, and support AI-driven healthcare solutions across commercial, medical, and R&D domains.

This execution-focused role offers exposure to client engagements and scalable data pipelines. You will collaborate with data science, consulting, and client teams to deliver analytics projects, ensure data quality, and

Qualifications

• Bachelor’s or master’s degree in engineering, Life Sciences, Analytics, or a related field.
• Minimum 2 years of pharma, life sciences consulting, or advanced analytics roles.
• Strong analytical and problem-solving skills with high motivation and attention to detail.
• Good verbal and written communication with the ability to present insights clearly.
• Understanding of client data privacy, compliance, and governance standards.
• Experience with pharmaceutical transactional datasets including sales and volume data, Rx data, specialty level data, and longitudinal patient level datasets.

Responsibilities

• Own patient journey analytics workstreams using claims/EHR, SQL, Python, and longitudinal RWD.
• Develop and deploy machine learning models, including predictive analytics, NLP, and basic deep learning use cases.
• Support AI-driven solutions for patient segmentation, sales force effectiveness, market access analytics, and clinical data analysis.
• Assist in building scalable and efficient data pipelines and analytics workflows.
• Perform data curation, transformation, and exploratory data analysis across healthcare datasets.
• Ensure data quality and compliance with privacy standards.
• Identify patterns and insights to support model development and business problems.
• Collaborate with cross-functional teams to deliver analytics projects.
• Translate business problems into analytical approaches with senior guidance.
• Contribute to documentation, model validation, and deployment processes.
• Support client deliverables including presentations, dashboards, and reports.
• Communicate analytical findings clearly to internal and client teams.
• Participate in client discussions to explain methodologies and insights.
• Stay updated with AI, ML, and healthcare analytics trends.
• Contribute to knowledge sharing and reusable assets.

Skills

SQL

Python

RWD

ML

NLP

Deep learning

Education

Bachelor’s or Master’s degree in engineering or Life Sciences

Job description

Role- Consultant / Senior Consultant / Project Manager – Advanced Analytics & AI

Notice Period- Immediate Joiner

Job Description

Our Values & Culture

At PharmaACE, we are committed to creating an environment where people can do meaningful work and be their authentic selves. We believe diverse perspectives strengthen the way we solve problems and deliver impact, and we strive to foster a culture grounded in respect, equity, and collaboration. As an equal opportunity employer, we ensure that our people practices from hiring to growth and development are fair, inclusive, and merit driven. We are continuously working towards building a workplace where every individual feels valued, supported, and empowered to grow.

Opportunity Overview

We are looking for a skilled and motivated professional in Advanced Analytics & Applied AI to support the delivery of AI driven solutions for pharmaceutical and healthcare clients. In this role, you will work closely with senior team members to develop, implement, and scale analytics solutions across commercial, medical, and R&D domains. This is an execution focused role with opportunities to build expertise in AI/ML while gaining exposure to client engagements.

What You'll Work On

• Own patient journey analytics workstreams using claims/EHR, SQL, Python, and longitudinal RWD; diagnose behavioural shifts impacting commercial demand.
• Develop and deploy machine learning models, including predictive analytics, NLP, and basic deep learning use cases under guidance from senior team members
• Support development of AI-driven solutions for use cases such as patient segmentation, sales force effectiveness, market access analytics, and clinical data analysis.
• Assist in building scalable and efficient data pipelines and analytics workflows.
• Perform data curation, transformation, and exploratory data analysis across diverse healthcare datasets (e.g., claims, Rx, CRM, EHR).
• Ensure data quality and consistency, adhering to compliance and data privacy standards.
• Identify patterns, trends, and insights to support model development and business problem solving.
• Work collaboratively with cross-functional teams (data science, consulting, and client teams) to deliver analytics projects.
• Translate business problems into analytical approaches with guidance from senior stakeholders.
• Contribute to documentation, model validation, and deployment processes.
• Support preparation of client deliverables, including presentations, dashboards, and reports.
• Communicate analytical findings in a clear and structured manner to internal and client teams.
• Participate in client discussions as needed to explain methodologies and insights.
• Stay updated with emerging trends in AI, machine learning, and healthcare analytics.
• Contribute to internal knowledge sharing, reusable assets, and best practices.

Required Qualifications

• Bachelor’s or master’s degree in engineering, Life Sciences, Analytics, or a related field..
• Minimum 2 years of experience in pharma, life sciences consulting, or advanced analytics roles
• Strong analytical and problem-solving skills with high motivation, initiative, and attention to detail
• Good verbal and written communication skills with the ability to present insights clearly
• Understanding of client data privacy, compliance, and governance standards.
• Experience working with pharmaceutical transactional datasets including sales and volume data, Rx data, specialty level data, and longitudinal patient level datasets.