The Role
Develops and validates data science algorithms and analytics solutions from requirements gathering through production deployment. Responsibilities include analytical problem formulation, data preparation, model development, risk analysis, design reviews, software development, fleet-level validation, documentation, stakeholder collaboration, customer handover, and deployment support. The role requires adherence to engineering standards, project requirements, review processes, and production release procedures.
Summary Generated by Built In
1.Collection of requirements and/or needs
2.Definition of the high-level scope/purpose of algorithm and application
3.Identification of the proper analytics framework to achieve the above-mentioned objectives
4.Algorithms/analytic development within assigned projects taking care of the technical standpoint, using sound engineering principles and adhering to standards, best practices, procedures, state-of-the-art technologies (including ML/AI) as well as product/program requirements. In detail:
·Collection of detailed requirements with all the necessary information and relevant updates into the predefined projects repository
·Risk analysis and revision of required process steps according to the risk level for the analytics in development within the project. Ensure mitigation action are in place if needed, comply with foreseen reviews
·Conceptual design and design concept review evaluating the level to which product requirements will be met with the proposed design
·Release plan definition and project documentation list preparation
·Software development process in incremental and rapid cycles
·Intermediate results review to assess design concept, technical risk and verify that product requirements will be met
·Analytics validation at fleet level as per final release acceptance criteria
·Final review to analyze residual risk and prove adherence to product requirements
·Verification, validation, and final implementation of analytics
·Analytics Release/Deploy in production environment
·Handover to customers
5.Project reviews attendance and report out preparation during project phases
6.Preparation of technical documentation consistent with engineering policies and procedures using companies' repository
Requirements understanding → analytical problem formulation → data preparation → algorithm/model development → validation → deployment support → documentation → stakeholder collaboration
Skills Required
- Requirements gathering and analytical problem formulation
- Data preparation and analytics framework selection
- Algorithm and machine learning model development
- Analytics verification and validation
- Production analytics deployment and release support
- Technical documentation and project repository maintenance
- Risk analysis and mitigation planning
- Stakeholder collaboration and customer handover
- Software development using engineering principles, standards, and best practices
Am I A Good Fit?
Get Personalized Job Insights.
Our AI-powered fit analysis compares your resume with a job listing so you know if your skills & experience align.
Success! Refresh the page to see how your skills align with this role.
The Company
What We Do
Proclink is a digital and AI transformation company that helps regulated and operationally intensive enterprises modernize systems, workflows, and decision environments. It combines strategy and consulting, data engineering, artificial intelligence, analytics, implementation and integration, managed services, and technology services. The company serves manufacturing, financial services, life sciences, and other regulated industries, delivering connected enterprise intelligence and measurable operational performance for clients.
