About the Company
Tiger Analytics is a fast-growing advanced analytics consulting firm, a trusted analytics partner for multiple Fortune 500 companies. We enable them to generate business value from data, recognized by market research firms like Forrester and Gartner for our business value and leadership.
About the Role
As a Lead Data Scientist at Tiger Analytics, you will be at the forefront of solving high-impact business problems using advanced machine learning, data engineering, and analytics solutions. This role demands a balanced mix of technical expertise, stakeholder management, and leadership. You will collaborate with cross-functional teams and business partners to define technical problem statements and hypotheses, develop efficient and accurate analytical models, and incorporate these into analytical data products and tools. You will drive current and future strategy by leveraging your analytical skills to ensure business value and effectively communicate results.
Key Responsibilities
- Analytical Translation: Translate complex business problems into sophisticated analytical structures, conceptualizing solutions anchored in statistical and machine learning methodologies.
- Problem Solving: Apply technical proficiency in data manipulation, statistical modeling, and machine learning to solve real-world business problems.
- Client Engagement: Establish a deep understanding of clients' business contexts, working closely to unravel intricate challenges and opportunities.
- Algorithmic Expertise: Develop and refine algorithms and models into powerful tools to surmount intricate business challenges.
- Quantitative Mastery: Conduct in-depth quantitative analyses, navigating vast datasets to extract meaningful insights that drive informed decision-making.
- Cross-Functional Collaboration: Collaborate seamlessly with multiple teams, including Consulting and Engineering, fostering relationships with diverse stakeholders to meet deadlines and bring Analytical Solutions to life.
Requirements
- 8+ years of relevant Data Science experience with a deep focus on US Pharmaceutical Marketing.
- Campaign Optimization: Proven track record in optimizing non-personalized, multichannel, and Omnichannel (HCP/Patient) marketing strategies.
- Journey Analytics: Deep understanding of Patient & Customer Journey mapping, media performance attribution, and behavioral segmentation.
- Advanced Analytics: Expertise in foundational ML (Regression, Classification, Optimization) with a nuanced understanding of statistical assumptions and limitations.
- Production-Grade Code: Proficiency in writing modular, scalable, and bug-free Python.
- The Data Stack: High proficiency in SQL and experience navigating Big Data environments (Spark, Hive, or Hadoop).
- MLOps & Cloud: Hands-on experience with version control (Git), containerization (Docker), and cloud ecosystems (AWS, Azure, or GCP).
- Stakeholder Influence: Ability to lead high-stakes analytics engagements and translate complex data findings into "so-what" insights for senior leadership.
- Communication: Exceptional presentation skills, capable of driving strategic conversations and building consensus across diverse organizational teams.
- Growth Mindset: A proactive hunger to learn emerging technologies and adapt to the evolving healthcare data landscape.