Data Scientist

SPECTRAFORCE; United States; On-site; USD 90,000 - 130,000; Full time

Job summary

SPECTRAFOR is looking for a highly motivated Data Scientist to develop data-driven solutions in the pharmaceutical commercial domain. Key responsibilities include developing predictive models and optimizing HCP engagement strategies.

The ideal candidate should have a Master’s or PhD in a quantitative discipline, with substantial experience in machine learning and GenAI implementations. Strong communication skills and experience in the pharmaceutical sector are crucial for success.

Qualifications

• 5-7+ years (Master’s) or 3–5+ years (PhD) in data science, machine learning, or advanced analytics.
• Proficiency in Python or R is preferred.
• Experience in pharmaceutical or life sciences analytics preferred.

Responsibilities

• Develop and deploy predictive models for patient events.
• Scale Next Best Action solutions for HCP engagement.
• Integrate GenAI into commercial workflows.

Skills

Machine Learning

GenAI frameworks

Python

Statistical analysis

Data privacy and regulatory standards

Education

Master’s or PhD in Data Science

Computer Science

Statistics

Tools

Databricks

AWS SageMaker

Power BI

Job description

We are seeking a highly motivated Data Scientist to join the organization within the pharmaceutical commercial domain. This role focuses on building data science and AI-driven solutions, including predictive patient event modeling, Next Best Action (NBA) engines for HCP engagement, and GenAI-powered decision agents to enhance commercial effectiveness.

The ideal candidate will combine strong machine learning expertise with experience in GenAI agent development and scalable ML pipelines, enabling actionable insights for stakeholders across GDDI, Sales, Marketing, Sales Analytics, and Advanced Analytics functions.

Key Responsibilities

• Develop and deploy predictive models for patient events (line switches, initiation)
• Scale Next Best Action (NBA) solutions to optimize HCP engagement strategies across channels to various products
• Apply advanced ML techniques including regression, classification, and NLP techniques
• Create multi touch attribution pipelines for the customer journeys and optimization
• Integrate GenAI capabilities into commercial workflows such as:
• Gen AI interfaces for ML pipelines
• Oversee build and maintenance of end-to-end ML pipelines including:
• Data ingestion, feature engineering, model training, evaluation, and deployment
• Model versioning, monitoring, and retraining pipelines
• Work with modern data platforms (e.g., Databricks, AWS)

Commercial Strategy & Stakeholder Support

• Partner with Sales, Marketing, and Sales Analytics teams to translate business problems into analytical solutions
• Deliver actionable insights and recommendations to senior stakeholders

Collaborate with

• Advanced Analytics teams (modeling and experimentation on alerts)
• Data Engineering teams (data pipelines and infrastructure)
• Business stakeholders (Sales, Marketing, Market Access)
• Act as a bridge between technical and business teams, ensuring adoption of advanced analytics and AI solutions

Data Management & Compliance

• Work with large-scale healthcare datasets such as:
• Claims, EHR/EMR, CRM, and digital engagement data
• Ensure compliance with data privacy and regulatory standards (e.g., HIPAA)

Required Qualifications

Education

• Master’s or PhD in:
• Data Science
• Computer Science
• Statistics
• Operations Research
• Mathematics or a related quantitative discipline

Experience

• 5-7+ years (Master’s) or 3–5+ years (PhD) in:
• Data science, machine learning, or advanced analytics
• Pharmaceutical / life sciences commercial analytics preferred
• Healthcare analytics or consulting experience

Technical Skills

Core Data Science

Proficiency in:

• Python (preferred) or R
• SQL

Strong understanding of:

• Machine learning algorithms (supervised/unsupervised learning)
• Statistical analysis and experimental design

GenAI & Modern AI Stack

Hands-on experience with:

• Large Language Models (LLMs) and GenAI frameworks
• Prompt engineering and RAG architecture
• Agent-based AI systems (e.g., LangChain, MCP, A2A, AutoGen)

Familiarity with:

• Vector databases and embeddings
• API-based AI integrations

Experience with:

• Tools such as Databricks, Azure ML, AWS SageMaker

Knowledge of:

• CI/CD pipelines for ML systems
• Ability to build apps for demo purposes using Databricks
• Experience with BI tools (Power BI, Tableau)
• Strong storytelling skills to communicate insights effectively

Pharmaceutical commercial domain experience, including

• Patient journey and longitudinal data analysis
• HCP targeting and segmentation
• Omnichannel marketing analytics and campaign optimization

Experience in

• Next Best Action (NBA) frameworks
• Promotional response modeling especially Multi- touch Attribution
• Strong problem-solving mindset with business acumen
• Ability to bridge AI innovation with commercial impact
• Excellent stakeholder management and communication skills
• Experience working in cross-functional, global teams
• High attention to detail and commitment to quality

What Success Looks Like

• Delivering scalable AI/ML and GenAI solutions that drive commercial insights
• Enabling smarter, real-time decision-making for Sales and Marketing teams
• Successfully deploying GenAI agents and production-grade ML pipelines

For information on benefits, equal opportunity employment, and location-specific applicant notices, click here

At SPECTRAFORCE, we are committed to maintaining a workplace that ensures fair compensation and wage transparency in adherence with all applicable state and local laws.