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Data Science Analyst, Complexity Analytics - Job Opportunity at Ford Motor Company

Norristown, United States
Full-time
Mid-level
Posted: February 12, 2025
Hybrid
USD 95,000 - 135,000 per year based on location and required experience level

Benefits

Comprehensive medical coverage with immediate eligibility - above industry standard
Enhanced family support with flexible care days and paid parental leave
Progressive fertility and family building benefits including adoption support
Employee vehicle purchase program with management lease options
Advanced professional development through tuition assistance
Generous PTO including year-end holiday shutdown
Complete dental and vision coverage
Back-up childcare subsidies

Key Responsibilities

Lead development of advanced analytics solutions for manufacturing complexity reduction
Drive strategic decision-making through AI/ML implementation in product portfolio
Collaborate cross-functionally to translate business requirements into technical solutions
Architect and deploy analytics products on Google Cloud Platform
Provide technical leadership in optimization and simulation techniques
Deliver data-driven insights to senior stakeholders

Requirements

Education

Master's degree in a quantitative field, such as Data Science, Engineering, Operations Research, Industrial Engineering, Statistics, Mathematics OR Computer Science

Experience

2+ years hands-on experience with mathematical programming, machine learning, artificial intelligence, optimization/simulation techniques, or statistical analysis

Required Skills

Mathematical programming Machine learning Artificial intelligence Optimization techniques Statistical analysis Agile methodology Data analytics Operations research Google Cloud Platform Communication skills
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Sauge AI Market Intelligence

Industry Trends

Automotive industry's accelerated shift toward data-driven manufacturing optimization Growing emphasis on complexity reduction through AI/ML in traditional manufacturing Increased integration of cloud-based analytics in legacy manufacturing systems Rising demand for cross-functional data scientists who can bridge business and technical domains

Role Significance

Likely part of a 5-8 person analytics team within larger GDIA organization
Mid-level individual contributor with potential for technical leadership

Key Projects

Manufacturing process optimization initiatives Complexity reduction programs through data analytics Legacy system modernization efforts Cross-functional analytics product development

Success Factors

Strong balance of technical expertise and business acumen Ability to translate complex technical concepts for non-technical stakeholders Experience with manufacturing systems and processes Proactive problem-solving approach in ambiguous environments

Market Demand

High demand role with significant growth potential due to automotive industry's digital transformation initiatives

Important Skills

Critical Skills

Manufacturing domain knowledge combined with advanced analytics expertise Experience with large-scale optimization problems Ability to work with both legacy and modern cloud systems Strong communication skills for stakeholder management

Beneficial Skills

Knowledge of automotive manufacturing processes Experience with Google Cloud Platform Understanding of compliance and regulatory requirements Product-driven development experience

Unique Aspects

Rare opportunity to apply advanced analytics in traditional manufacturing setting
Direct impact on global manufacturing efficiency
Exposure to both legacy systems and cutting-edge cloud technologies

Career Growth

2-3 years in role before advancement opportunity, depending on project impact and leadership development

Potential Next Roles

Senior Data Scientist Technical Product Manager Analytics Team Lead Manufacturing Analytics Architect

Company Overview

Ford Motor Company

Traditional automotive manufacturer undergoing significant digital transformation

Leading global automotive manufacturer with strong focus on technology innovation
Major presence in PA region with significant investment in digital capabilities
Traditional manufacturing culture evolving toward data-driven decision making with emphasis on innovation
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