ROLE SUMMARY

Associate Data Scientist is responsible to assist Pfizer’s Data Management staff to leverage both internal and external data assets to deliver business insights, implement automation and Artificial Intelligence (AI) methods by collaborating with cross-functional teams within the organization with an overall goal of enhancing tactical and strategic decision making.

This role requires a good understanding of technical and business aspects of Data Science, Clinical Trial data, and Data Management. Exposure to Artificial Intelligence (AI) tools and techniques is a plus. Must be able to understand the analytical needs of business users, to translate the business needs into automation solutions. Requires full Data Science life cycle development experience, including data discovery, labelling the data, working with tech team(s) to create hypothesis, assist in selecting models, test and evaluate models and model operationalization. Should have a strong understanding of relational databases and Clinical Trial data to facilitate data wrangling, model operationalization, and exploration of data. Responsible for adhering to corporate reporting policy and controls to ensure the accuracy, timeliness and confidentiality of Data Management automation. Data scientist must be able to drive tangible business value working under the direction of Lead for AI and Data Sciences by collaborating with Data Managers, Clinical Data Scientists, Client Partners and Information Management colleagues and external vendors.

ROLE RESPONSIBILITIES

General:

Assist the manager implement global strategies, initiatives, processes, and standards to ensure consistent, efficient, and quality Data Science processes to meet expected quality, timelines and deliverables.

Run SQL queries to extract Operational, Clinical data and Specifications from various information systems.

Able to independently assess and analyze data quality, understand business processes and how they impact data quality, prepare data including labelling of data for Machine Learning experiments.

Able to pilot and build POC’s to demonstrate and test business value of Machine Learning models, understand Model metrics, iteratively improve Model performance working with tech leads and vendors.

Analyze, interpret, and summarize Machine Learning model results.

Operationalize and maintain the models.

Develop presentations and trainings for business users to increase understanding of AI, Data Science and automation within Data Management.

BASIC QUALIFICATIONS:

Bachelor’s degree or above in Informatics, or Computer science, or Statistics, or related business degree with equivalent experience preferred
Up to two years of total experience with Clinical data, SQL, and Analytics.
Works independently, receives instruction primarily on unusual situations
Ability to organize tasks, time and priorities; ability to multi-task
Ability to communicate with internal & external stakeholders, locally and globally

PREFERRED QUALIFICATIONS:

Demonstrated experience with Python and/or R, SAS and Machine Learning models implementation
SQL experience with relational databases like Postgres or Oracle or Microsoft.
Prior experience working with Clinical Trials data in large or midsize companies preferred.
Be able to manage multiple tasks simultaneously and react to problems quickly.
Must have excellent verbal and written communication skills.
Must have solid theoretical understanding of classical machine learning as well as Deep Learning methods, NLP and Knowledge Graphs
Must be a team player, with good listening abilities, self-motivated and demonstrate results.
Prior working experience with teams spread across different time zones is a plus.

Work Location Assignment: Hybrid

Please apply by sending your CV and a motivational letter in English

This role is posted in multiple locations. If you are applying for the role in an secondary job posting location where pay transparency regulations apply, your Talent Advisor will share the local pay information with you during the first interview.

Purpose

Breakthroughs that change patients' lives... At Pfizer we are a patient centric company, guided by our four values: courage, joy, equity and excellence. Our breakthrough culture lends itself to our dedication to transforming millions of lives.

Digital Transformation Strategy

One bold way we are achieving our purpose is through our company wide digital transformation strategy. We are leading the way in adopting new data, modelling and automated solutions to further digitize and accelerate drug discovery and development with the aim of enhancing health outcomes and the patient experience.

Flexibility

We aim to create a trusting, flexible workplace culture which encourages employees to achieve work life harmony, attracts talent and enables everyone to be their best working self. Let’s start the conversation!

Equal Employment Opportunity

We believe that a diverse and inclusive workforce is crucial to building a successful business. As an employer, Pfizer is committed to celebrating this, in all its forms – allowing for us to be as diverse as the patients and communities we serve. Together, we continue to build a culture that encourages, supports and empowers our employees.

Disability Inclusion

Our mission is unleashing the power of all our people and we are proud to be a disability inclusive employer, ensuring equal employment opportunities for all candidates. We encourage you to put your best self forward with the knowledge and trust that we will make any reasonable adjustments to support your application and future career. Your journey with Pfizer starts here!

Pfizer endeavors to make www.pfizer.com/careers accessible to all users. If you would like to contact us regarding the accessibility of our website or need assistance completing the application process and/or interviewing, please email disabilityrecruitment@pfizer.com. This is to be used solely for accommodation requests with respect to the accessibility of our website, online application process and/or interviewing. Requests for any other reason will not be returned.

To learn more about acceptable and prohibited uses of AI during the recruitment process, please review our candidate AI-use guidelines available on Pfizer Careers.

Medical

919 Pfizer Hellas AE

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