Role Summary

　　Do you want to make an impact on patient health around the world? Do you thrive in a fast-paced environment that brings together scientific, clinical, and commercial domains through engineering, data science, and analytics? Then join Pfizer Digital's Artificial Intelligence, Data, and Analytics organization (AIDA) where you can leverage cutting-edge technology to inform critical business decisions and improve customer experiences for our patients and physicians. Our collection of engineering, data science, and analytics professionals are at the forefront of Pfizer's transformation into a digitally driven organization leveraging data science and advanced analytics to change patient's lives. The Industrialization team within Data Science Solutions and Initiatives leads the scaling of data and insights capabilities - critical drivers and enablers of Pfizer's digital transformation.

　　As the Director, Data Science And Advanced Analytics Japan Tech Lead, you will be a leader within the Data Science Industrialization team that leverages best practices from software engineering, data science, and analytics engineering to accelerate data-driven insight generation across the pharma value chain. In this role, you will be a technical advisor for developing and enhancing data science and advanced analytics applications and integrating them into the enterprise analytics platform. You will help guide the strategic direction for advanced analytics within the Japan Biopharma team while counseling business teams on how to evolve Pfizer Japan into a data-driven organization. In this process, you will work on diverse projects to close the loop between decisionmakers and data by leveraging software engineering best practices to develop applications with embedded analytics and data science processes. You will also integrate globally with Pfizer advanced analytics teams to elevate analytics assets to organizational or enterprise solutions for use at Pfizer. The ideal candidate is an expert in software engineering and data science with experience working in diverse and cross-functional teams, bridging the gap between data, technology, and people, to deliver the promise of AI/ML to improve patients' lives.

　　Role Responsibilities

　　Provide thought leadership in envisioning and developing scalable data science solutions to transform Pfizer's go-to-market modelLead data science solutions development work streams by providing expertise, thought leadership, and embodying best practices to drive technical and strategic objectivesDesign and deliver data science and advanced analytics solutions which embed rigorous statistical methods and machine learning techniquesOversee the roadmap for reusable assets and custom pipelines by identifying and implementing operational efficiencies in analytics executionMentor junior team members through technical and organizational thought leadership and innovationResearch, identify, and apply new algorithms and technologies to solve complex problems and systematize solutions into reusable assets and capabilitiesLead Agile-based project management standards (i.e. daily check-in procedures, workload status, and cost overruns/projections)Inform data science product development and activation in commercial market

　　Qualifications

　　Must-Have

　　10+ years of work experience as a software engineer and tech lead for a diverse range of projects5+ years of hands-on expertise in data science projects or software development2+ years experience as a back-end or full-stack senior/staff/principal software engineer

　　Computer Science, Engineering, Mathematics, or Statistics majors with data science or software development specialization - Computer Science, Engineering, Analytics etc.Lead, design, and conduct advanced data analysis, predictive analytics, formulate mathematical approaches, and design complex algorithms to solve business problemsUnderstanding of data science development lifecycle (CRISP)Experience in data ingestion, data warehousing, and data model conceptsStrong hands-on skills in a cloud based analytics ecosystem (AWS, Snowflake, etc)Strong hands-on skills in CI/CD integration (e.g. GitHub, GitHub Actions or Jenkins)Strong hands-on skills in containerization (e.g. AWS EKS, Kubernetes)Strong hands-on skills for data pipeline orchestration (e.g. Airflow)Strong hands-on skills in ML engineering and data science (e.g., Python, industrialized ETL software)Experience with big data technologies (e.g. Spark)Experience with test-driven development and automated testing frameworks (e.g.pytest, Selenium)Deep understanding of MLOps principles and tech stack (e.g. MLFlow)Superior analytical skills required; Strong verbal and written communication skillsDemonstrated experience interfacing with other internal and external teams to incorporate their innovations and vice versaExperience in developing and operating analytic workflows and model pipelines that are parametrized, automated and reusableExperience developing and deploying data and analytic products for use by technical and non-technical audiencesContinuous improvement: research industry leading analytics practicesLead discussions in cross functional forums and effectively clarify model design, deployment, insights, and implications to all cohorts of usersRepresent the company in industry events and help recruit top talentFierce curiosity, strong analytical skills, and strong sense of ownership in problem solvingBuild a sense of trust and rapport that creates a comfortable and effective workplace, and an ability to work as part of an agile team (product owner, developers, etc.)

　　Nice-to-Have

　　Knowledge of business processes in commercial pharmaceutical domains would be strong plusDeep expertise with data science enabling technology, such as Dataiku Data Science Studio, AWS SageMaker, Domino Data lab, or other data science platformsIndustry or consulting experience, along with project management skills strongly preferredJapanese and English language proficiency

　　Work Location Assignment: Flexible

　　Pfizer is an equal opportunity employer and complies with all applicable equal employment opportunity legislation in each jurisdiction in which it operates.

　　Information & Business Tech

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