Job Title: Senior/Lead Data Scientist Pharma
Location: New York/New Jersey
Who we are
Tiger Analytics is a global leader in AI and analytics helping Fortune 1000 companies solve their toughest
challenges. We offer full-stack AI and analytics services & solutions to empower businesses to achieve real
outcomes and value at scale. We are on a mission to push the boundaries of what AI and analytics can do to
help enterprises navigate uncertainty and move forward decisively. Our purpose is to provide certainty to
shape a better tomorrow.
Curious about the role What would your typical day look like
As a Senior/Lead Data Scientist your role will involve
Analytical Translation: Translate complex business problems into sophisticated analytical structures
conceptualising solutions anchored in statistical and machine learning methodologies.
Problem Solving: While technical proficiency in data manipulation statistical modelling and machine
learning is crucial the ability to apply these skills to solve real-world business problems is equally
vital.
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 sculpting them 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
What do we expect
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.
Job Title: Senior/Lead Data Scientist Pharma Location: New York/New Jersey Who we are Tiger Analytics is a global leader in AI and analytics helping Fortune 1000 companies solve their toughest challenges. We offer full-stack AI and analytics services & solutions to empower businesses to achieve...
Job Title: Senior/Lead Data Scientist Pharma
Location: New York/New Jersey
Who we are
Tiger Analytics is a global leader in AI and analytics helping Fortune 1000 companies solve their toughest
challenges. We offer full-stack AI and analytics services & solutions to empower businesses to achieve real
outcomes and value at scale. We are on a mission to push the boundaries of what AI and analytics can do to
help enterprises navigate uncertainty and move forward decisively. Our purpose is to provide certainty to
shape a better tomorrow.
Curious about the role What would your typical day look like
As a Senior/Lead Data Scientist your role will involve
Analytical Translation: Translate complex business problems into sophisticated analytical structures
conceptualising solutions anchored in statistical and machine learning methodologies.
Problem Solving: While technical proficiency in data manipulation statistical modelling and machine
learning is crucial the ability to apply these skills to solve real-world business problems is equally
vital.
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 sculpting them 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
What do we expect
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.
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