Senior Data Analyst, Assay Data at MSD
Praha, Praha, Czech -
Full Time


Start Date

Immediate

Expiry Date

28 May, 25

Salary

0.0

Posted On

01 Mar, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Data Visualization, Data Modeling, Analytical Skills, Scientists, Database Systems, Data Warehouse, Operational Support, Business Intelligence

Industry

Information Technology/IT

Description

Job Description
The role will assist Product Technical Leads in delivering the strategy for the Experiment Design and Execution (EDE) Product Line within Animal Health Research & Development IT. The role offers the chance to work on products that directly impact how lab-based research is conducted and accelerate innovative drugs to market. You will be comfortable collaborating with all levels of scientific and R&D IT EDE product team, to analyze and distil technical workflows from which to implement requirements. Success will be the acceptance and adoption of these new solutions by the scientists targeted for each release.
You must be able to empathize with our scientists’ needs and be a passionate advocate for their perspectives through all phases of product development. Collaboration will be a key aspect of your role as you work closely with cross-functional teams, including researchers, data scientists and IT professionals. Together with an agile team, you will develop efficient and scalable data solutions for our R&D laboratories to capture assay data. Your bioscientific background and your expertise in data engineering and IT will play a critical role in accelerating processes and data flows and foster the discovery and development of new veterinary medicines.

REQUIREMENTS

  • Minimum Bachelor’s in a field related to Biosciences
  • Minimum of 5 years’ work experience, with demonstrated expertise in scientific IT solutions like Activity Base, Genedata, etc.
  • Strong analytical skills with a creative mindset
  • Strong communication and collaboration skills
  • Understanding of database systems, data modelling, and data warehouse concepts
  • Ability to quickly grasp new technological and scientific concepts
  • Ability to demonstrate curiosity and flexible thinking to get to the underlying issue and define the problem
  • Ability to demonstrate analytical problem-solving skills and the ability to work with varying levels of ambiguity across multiple projects concurrently
  • Strong written and verbal communications skills and the ability to interact with both technical and non-technical stakeholders and users
  • Ability to work in a team of multidisciplinary scientists and IT personnel, and operate effectively in a matrix environment; team player yet able to work independently
  • Experience providing ongoing operational support for scientific research applications
  • Experience in Data Warehouse and Data Lake storage architectures for scientific research data
  • Demonstrable knowledge of problems facing scientists working a drug discovery lab
  • Familiarity with cloud-based software and terms
  • Familiarity with agile software development processes

KNOW ANYBODY WHO MIGHT BE INTERESTED? REFER THIS JOB!

Current Employees apply HERE
Current Contingent Workers apply HERE

REQUIRED SKILLS:

Business Intelligence (BI), Data Management, Data Modeling, Data Visualization, Measurement Analysis, Stakeholder Relationship Management, Waterfall Model

Responsibilities
  • Design efficient end-to-end data workflows to support pharmaceutical and vaccine research
  • Support data capture, transformation, and analysis of R&D data (e.g. biochemical / biological assay data)
  • Provide day to day support function to the EDE Product Team, ensuring user success of developed solutions
  • Conduct user interviews/analyses and work with support teams to identify problems and document them
  • Work with IT and lab-based staff to proactively map these workflows and needs
  • Synthesize data, observations, and other research into insights to help inform product strategy and decisions
  • Author technical requirements, test scripts and user facing documentation
  • Work with offshore/remote teams and software vendors to implement requirements
  • Streamline workflows, reduce manual transcriptions, and enhance workflow efficiency
  • Develop data capture forms and ingestion pipelines to process information from diverse R&D data sources
  • Design meaningful and reusable data components, that can be applied across different projects and datasets
  • Enable data integration, interoperability, and discoverability through the application of FAIR principles
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