Machine Learning Engineering Lead - 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 patients' 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

Set a vision and provide daytoday leadership, supervision, and mentorship for a team of individual contributors with functional expertise that includes analytics, data science, ML Ops, and engineering
Interface with Enterprise Architecture team to operationalize the vision of MLOps enablement
Build ML engineering capabilities and contribute to the broader talent building framework
Provide direction for ML engineering research, design, and implementation of best practices, and facilitate related trainings
Provide strategic and technical input for data science industrialization roadmap
Provide input on platform evolution, vendor scan, and overall data science industrialization capability roadmap development
Lead the advancement of at scale MLOps enablement across bespoke analytics
Lead ML engineering deployments to enable production models across the ML lifecycle including model training, monitoring, and retraining where required
Lead ML engineering deployments to enable production models across the ML lifecycle including model training, monitoring, and retraining where required
Lead implementation of CI/CD orchestration for data science pipelines
Partner with AIDA Data team to integrate developed ML pipelines into enterpriselevel analytics data products where appropriate
Partner with AIDA Platforms team on continuous development and end to end capability integration between OOB platforms and internal engineered components (API registry, ML library / workflow management, enterprise connectors); Performance and resource optimization of managed pipelines and models

BASIC QUALIFICATIONS

Bachelor's degree in ML engineering related area (Data Science, Computer Engineering, Computer Science, Information Systems, Engineering or a related discipline)
7+ years of work experience in data science, analytics, or engineering for a diverse range of projects
Deep expertise with data science enabling technology, such as Dataiku Data Science Studio, AWS SageMaker or other data science platforms
Strong understanding of data science development lifecycle (CRISP)
Strong handson skills in ML engineering and data science (e.g., Python, industrialized ETL software)
Deep understanding of MLOps principles and tech stack (e.g. MLFlow)
Experience working in a cloud based analytics ecosystem (AWS, Snowflake, etc)
Experience in CI/CD integration (e.g. GitHub, GitHub Actions or Jenkins)
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
23 years of handson experience leading data science or ML engineering teams
Hands on experience working in Agile teams, processes, and practices
Experience in solution architecture & design
Experience in software/product engineering
Strong handson skills for data and machine learning pipeline orchestration via Dataiku (DSS 9 or 10) platform
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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