Data Science Industrialization, Analytics - San José, Costa Rica - Pfizer

Pfizer

Empresa verificada

San José, Costa Rica

hace 1 semana

Publicado por:

Andrea Rodríguez

beBee Recruiter

Descripción

Recruiter

Pfizer
Location

Escazu, Costa Rica

Costa Rica
Costa Rica
Salary
Competitive
Posted
05 Jun 202 Closes
05 Jul 202 Ref
Sector
Science and Pharmaceutical
Contract Type
Permanent
Hours
Full Time

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 Enterprise Data Science and Advanced Analytics leads the scaling of data and insights capabilities - critical drivers and enablers of Pfizer's digital transformation.

ROLE RESPONSIBILITIES

Develop, maintain, and advance at scale "industrialized" data science capabilities and analytic products
Develop and maintain parametrized workflows, data sets, and reusable widgets in the delivery of AI/ML analytic insights products
Provide analytics engineering expertise to data science agile teams
Implement CI/CD orchestration for data science pipelines
Translate data needs into intro programable queries and convert Python based data wrangling code into PySpark/SQL pipelines for scalable pushdown execution
Conduct basic data profiling and quality checks
Develop automated and selfmonitoring data pipelines including automated QA/QC processes
Work with stakeholders to assist with datarelated technical issues and support data infrastructure needs
Create and maintain robust technical documentation for these industrialized assets to enable knowledge retention and sharing

BASIC QUALIFICATIONS

Bachelor's degree in analytics engineering related area (Data Science, Computer Engineering, Computer Science, Information Systems, Engineering or a related discipline)
5+ years of work experience as an analyst/analytics engineer
Strong handson skills in analytics engineering and data science (e.g., Python, R, SQL, industrialized ETL software)
Experience working in a cloud based analytics ecosystem (AWS, Snowflake, etc)
Experience working with various types of data (structured / unstructured)
Understanding of data ingestion, data warehousing, and data model concepts
Knowledge of relational and dimensional data structures, theories, and practices
Highly selfmotivated to deliver both independently and with strong team collaboration
Ability to creatively take on new challenges and work outside comfort zone
Strong English communication skills (written & verbal)

PREFERRED QUALIFICATIONS

Advanced degree in Data Science, Computer Engineering, Computer Science, Information Systems or related discipline
Strong handson skills in Javascript libraries/frameworks for visualization (D3, React, Angular)
Experience with AI/machine learning enabling technology, such as: Data Science Studio or equivalent data science platforms, Python, R, and visualization techniques
Hands on experience working in Agile teams, processes, and practices
Experience in CI/CD integration (e.g. Git Hub, Git Hub Actions or Jenkins)
Experience in software/product engineering
Handson experience in containerization (e.g. AWS EKS, Kubernetes)
Handson experience with data pipeline orchestration (e.g. Airflow)
Understanding of data science development lifecycle (CRISP)
Experience in developing and operating analytic workflows and model pipelines that are parametrized, automated and reusable
Experience developing and deploying data and analytic products for use by technical and nontechnical audiences
Pharma & Life Science commercial functional knowledge
Pharma & Life Science commercial data literacy
Experience with Dataiku Data Science Studio

#LI-PFE

PHYSICAL/MENTAL REQUIREMENTS
None

NON-STANDARD WORK SCHEDULE, TRAVEL OR ENVIRONMENT REQUIREMENTS
Ability to work non-traditional work hours interacting with global teams spanning across the different regions (eg: North America, Europe, Asia)

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

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