Job Description

Core Responsibilities

Perform advanced statistical analysis and develop machine learning models. Collaborate closely with analytics teams, including data engineers and senior data scientists.

Technical Skills

Strong command of Python is essential; knowledge of SQL is highly preferred. Experience working with large database systems such as MS SQL Server, or Oracle is valued.


Professional ExperienceMinimum of three years' experience in analytics roles. Direct involvement in at least one or two domains such as Manufacturing, Commercial, Procurement, R&D, HR, or Finance.


Manufacturing AnalyticsEmphasis on addressing analytics challenges in manufacturing, including optimizing processes and predictive maintenance.

Process OptimizationDevelop and implement analytics solutions to enhance manufacturing efficiency, streamline processes, and lower costs.


Capability Building (For Senior DSs, if any)Lead small teams of associate data scientists and mentor junior colleagues. Promote a culture of knowledge sharing and continuous learning within the team.

Key Interview Areas for Data Scientist Candidates

Technical ProficiencyEvaluate the candidate's expertise in Python and SQL. Assess experience with large database systems and ability to develop statistical and machine learning models.


Manufacturing Analytics ExperienceReview hands-on experience in resolving analytics issues in manufacturing, such as process optimization and predictive maintenance.

Problem-Solving SkillsExamine ability to perform advanced statistical analysis, create models using various learning techniques, and break down complex problems into manageable components.


Communication SkillsAssess ability to clearly convey complex analytical and technical concepts to both technical and non-technical audiences.

Team Leadership and CollaborationEvaluate experience in leading small teams, working with senior data scientists, and collaborating effectively in agile, multi-stakeholder environments.


Capability Building* Look for evidence of mentoring junior team members, promoting knowledge sharing, and fostering a culture of ongoing learning and innovation.