Labelling Data Scientist

Recruiter
Pfizer
Location
Tadworth
Salary
Negotiable
Posted
10 May 2021
Closes
25 May 2021
Ref
4813650
Hours
Full Time
Contract Type
Permanent

JOB SUMMARY

The Labelling Data Scientist is responsible for addressing critical data-related business problems by creating strategies to analyse, connect and draw conclusions from Pfizer systems, data lakes and external sources using robust data science techniques. Working with Business subject matter experts, the role will be familiar with labelling standards and compliance measures and will play a key role in supporting portfolio decision making and process development. The Labelling Data Scientist is also a critical contributor to discussions around data architecture and standards directed by Information Management (IM) and Digital.

The Data Scientist interprets and analyses data to provide innovative solutions to problems, designs data modelling processes to create algorithms and predictive models or performs custom analysis as required. The Labelling Data Scientist will support and/or direct initiatives relating to machine learning and artificial intelligence, representing Global Regulatory Affairs in discussions with Information Management and Digital.

The Labelling Data Scientist will be responsible for effective compliance monitoring and support time-critical provision of analysis of labelling data.

The role also acts as a key interface with IM providing SME for system requirements and data quality. In addition, you will be expected to lead or participate in imitative to improve efficiencies.



JOB RESPONSIBILITIES

· Proactively identify and extract valuable data from multiple sources and automate collection processes

· Participant in data governance committees

· Undertake pre-processing of structured and unstructured data

· Sift and analyze data from multiple angles, looking for trends that highlight problems or opportunities

· Builds and implements predictive models and machine-learning algorithms

· Use a combined knowledge of computer science and applications, modelling, statistics, analytics and maths to solve problems

· Maintain effective relationships with other platform lines and Business Units enabling facilitation of effective portfolio delivery

· Present information using data visualization techniques

· Become a subject matter expert in 1-2 digital. Automation skillsets (e.g. functionality mapping, predictive analysis)

· Create awareness by working across functions to share and learn about best practices.

· Lead or participate in International Labelling Group and or Global Regulatory Operations technology initiatives

· Developing best suited data models and algorithms in collaboration with Information Management and Digital partners

· Assessing the effectiveness of the data model with the ability to select the right technique of data gathering.

· Advocates data quality across systems and leads periodic data reviews and data optimization

· Point of contact for labelling compliance data.

· Takes appropriate risks to advance new concepts and methodologies for the design and optimization of data analytic projects.

· Use modelling to create the optimized customer experience.



QUALIFICATIONS / SKILLS

· Excellent communication (verbal, written) and presentation skills

· Proven experience as a Data Scientist or Data Analyst

· Proficient in existing digital tools and processes (e.g. Power Automate)

· Connective thinker, able to challenge and suggest optimization through data and insights.

· Experience in small to medium scale digital projects.

· A working knowledge of software programming

· Experience in data mining and analyzing

· Understanding of machine-learning and operations research

· Experience using business intelligence tools and data frameworks

· Analytical mind and business acumen

· Strong math skills (e.g. statistics, algebra)

· Problem-solving aptitude

· Ability to be flexible, adapt to change work freely, as well as part of a team in a matrix environment.

· Ability to present and communicate with peers and stakeholder.

· BSc/BA in Computer Science, or relevant field; graduate degree in Data Science or another quantitative field is preferred