Senior Consultant, Data Science – Elevate – Healthcare & Life Sciences

About the role

Simon-Kucher is a global management consulting firm specializing in strategy, marketing, pricing, and sales. We help healthcare and life sciences organizations optimize their commercial strategies and achieve profitable growth.

Responsibilities

• Deliver high-quality outputs and client-ready deliverables that meet and exceed client expectations.
• Work in teams across a wide variety of healthcare and life sciences clients, products, and project types, including pharmaceutical, biotech, medtech, payer, provider, healthcare technology, analytics, digital, commercial, market access, medical, and strategy engagements.
• Analyze and interpret healthcare and life sciences data to support pricing, market access, sales, launch, and commercial strategies; identify opportunities; and develop actionable recommendations linked to revenue growth, market access, patient impact, launch success, and commercial performance.
• Support data science engagements and analytical workstreams by contributing to high-quality analysis, rigorous methodology, clear documentation, analytical frameworks, financial models, quality assurance, and actionable recommendations.
• Support AI solution and agent development and implementation strategy, including patient and provider segmentation, next-best-action, forecasting, demand modeling, pricing analytics, promotional effectiveness, and real-world data analytics.
• Apply theoretical knowledge to develop predictive models using modern statistical, mathematical, machine learning, and artificial intelligence techniques.
• Conduct predictive analyses by selecting, testing, and applying appropriate modeling methods.
• Support the development of innovative strategies for pricing, marketing, and sales using expertise in machine learning, artificial intelligence, analytics, and healthcare and life sciences industry knowledge.
• Prepare compelling presentations, reports, and client-ready deliverables that communicate findings and recommendations clearly and impactfully to senior and executive audiences.
• Participate in client meetings, workshops, discussions, and presentations through exceptional service and effective communication.
• Support the development of materials for healthcare and life sciences analytics engagements, including research, analysis, pitch materials, and client discussion documents.
• Stay current with emerging research, market changes, and the latest data trends, while actively engaging in team discussions, workshops, and training sessions.
• Contribute innovative ideas, creative solutions, healthcare and life sciences analytics offerings, thought leadership, and reusable assets that address client business challenges and capitalize on market opportunities.
• Collaborate with internal and external business and technology experts from around the world as part of a growing, multicultural team.
• Engage in workshops and training sessions to enhance consulting and business acumen, technical expertise, healthcare and life sciences knowledge, and understanding of Simon-Kucher methodologies.
• Contribute to a collaborative and inclusive environment that fosters belonging for all.

Requirements

• Undergraduate and/or graduate degree from an accredited university or college in economics, computer science, engineering, business, statistics, marketing, finance, math, or related field.
• 2+ years of relevant full-time work experience in AI, data science, analytics and digital in consulting and/or commercial functions (e.g. pricing, marketing, sales), ideally with exposure in healthcare and life sciences.
• Strong hands-on proficiency in Python and SQL, including data cleaning, exploratory analysis, feature engineering, model development, analysis, and automation.
• Experience with visualization tools such as Power BI and/or Tableau, relational databases, ETL processes, and data engineering concepts.
• Strong technical foundation in statistical modeling, machine learning, and predictive modeling, with practical experience selecting, validating, and explaining models for business use cases.
• Familiarity with commonly used modeling techniques such as linear regression, logistic regression, support vector machines, decision trees, random forests, XGBoost, CatBoost, LightGBM, and other supervised learning approaches.
• Familiarity with common cloud-based machine learning platforms such as AWS SageMaker, Google Cloud Vertex AI, and Azure Machine Learning.
• Experience working with healthcare and life sciences data sources such as claims, EHR/EMR, prescription, patient-level, provider, payer, market access, CRM, promotional, real-world data, or clinical data is preferred.
• Familiarity with commercial challenges in healthcare and life sciences, including launch strategy, pricing, access, segmentation, forecasting, promotional effectiveness, patient journeys, and provider engagement.
• Proven experience analyzing and solving complex business problems using well-developed quantitative, conceptual, and analytical problem-solving skills, with the ability to define clear, actionable recommendations.
• Excellent communication and presentation skills, with fluency in English, both written and verbal, and a client-focused attitude.
• Proactive, self-motivated, and able to work both independently and collaboratively in a fast-paced environment.
• Sharp, analytical, and structured problem-solving mindset.
• Strong collaboration, teamwork, and project management skills.
• Proficiency in Microsoft Office Suite, including Word, Excel, PowerPoint, and Outlook.
• Ability to work from the office or client site 2–3 days per week in alignment with the hybrid working model.

Qualifications

• Undergraduate and/or graduate degree from an accredited university or college in economics, computer science, engineering, business, statistics, marketing, finance, math, or related field.
• 2+ years of relevant full-time work experience in AI, data science, analytics and digital in consulting and/or commercial functions (e.g. pricing, marketing, sales), ideally with exposure in healthcare and life sciences.
• Strong hands-on proficiency in Python and SQL, including data cleaning, exploratory analysis, feature engineering, model development, analysis, and automation.
• Experience with visualization tools such as Power BI and/or Tableau, relational databases, ETL processes, and data engineering concepts.
• Strong technical foundation in statistical modeling, machine learning, and predictive modeling, with practical experience selecting, validating, and explaining models for business use cases.
• Familiarity with commonly used modeling techniques such as linear regression, logistic regression, support vector machines, decision trees, random forests, XGBoost, CatBoost, LightGBM, and other supervised learning approaches.
• Familiarity with common cloud-based machine learning platforms such as AWS SageMaker, Google Cloud Vertex AI, and Azure Machine Learning.
• Experience working with healthcare and life sciences data sources such as claims, EHR/EMR, prescription, patient-level, provider, payer, market access, CRM, promotional, real-world data, or clinical data is preferred.
• Familiarity with commercial challenges in healthcare and life sciences, including launch strategy, pricing, access, segmentation, forecasting, promotional effectiveness, patient journeys, and provider engagement.
• Proven experience analyzing and solving complex business problems using well-developed quantitative, conceptual, and analytical problem-solving skills, with the ability to define clear, actionable recommendations.
• Excellent communication and presentation skills, with fluency in English, both written and verbal, and a client-focused attitude.
• Proactive, self-motivated, and able to work both independently and collaboratively in a fast-paced environment.
• Sharp, analytical, and structured problem-solving mindset.
• Strong collaboration, teamwork, and project management skills.
• Proficiency in Microsoft Office Suite, including Word, Excel, PowerPoint, and Outlook.
• Ability to work from the office or client site 2–3 days per week in alignment with the hybrid working model.

Skills

• Python
• SQL
• Data cleaning
• Exploratory analysis
• Feature engineering
• Model development
• Analysis
• Automation
• Visualization tools (Power BI, Tableau)
• Relational databases
• ETL processes
• Data engineering concepts
• Statistical modeling
• Machine learning
• Predictive modeling
• Supervised learning approaches
• Cloud-based machine learning platforms (AWS SageMaker, Google Cloud Vertex AI, Azure Machine Learning)
• Healthcare and life sciences data sources (claims, EHR/EMR, prescription, patient-level, provider, payer, market access, CRM, promotional, real-world data, clinical data)
• Commercial challenges in healthcare and life sciences (launch strategy, pricing, access, segmentation, forecasting, promotional effectiveness, patient journeys, provider engagement)
• Quantitative, conceptual, and analytical problem-solving skills
• Communication and presentation skills
• Microsoft Office Suite (Word, Excel, PowerPoint, Outlook)

Benefits

• Comprehensive benefits package including paid time off, 13 paid holidays, medical, dental, and vision coverage, life insurance, and a 401(k) plan.
• Total compensation for this role includes base salary, performance bonus, eligibility for annual merit-based increases, and a comprehensive benefits package.
• The base salary range for this position is between $125,000 to $150,000 per year for US roles.
• Specific compensation within these ranges will depend on factors such as experience, skills, and location.
• Salary ranges are reviewed periodically to ensure alignment with market conditions.

Pay

• The base salary range for this position is between $125,000 to $150,000 per year for US roles.
• Specific compensation within these ranges will depend on factors such as experience, skills, and location.
• Salary ranges are reviewed periodically to ensure alignment with market conditions.

Schedule

• Flexible working hours and a hybrid working model, allowing employees to work from the office or client site 2–3 days per week.

Simon-Kucher

Simon-Kucher is a global consultancy with over 2,200 employees in 30+ countries. Our sole focus is on unlocking better growth that drives measurable revenue and profit for our clients. As a trusted commercial advisor, we combine deep consulting expertise, growth specialization, and technology to scale impact. We optimize every lever of commercial strategy – product, pricing, innovation, marketing, sales, and digital – based on deep insights into what customers value and are willing to pay for. With over 40 years of experience in monetization, we are regarded as the world’s leading commercial growth and pricing specialist. Simon-Kucher is an Equal Employment Opportunity (“EEO”) employer. Our employment decisions are made without regard to race, color, religion, gender, national origin, age, disability, marital status, veteran or military status, or any other legally protected status. We believe in building a culture that embraces belonging, creating an environment in which our people feel valued, are able to be themselves and feel their contribution matters. If we get that right, great things will happen; people will grow faster, innovate, feel valued, and create better outcomes for everyone – our people, our clients and, of course, our business.