Data Scientist, Principal

Cummins Inc.

. Lead advanced analytics initiatives to solve complex business problems using quantitative analysis, statistical modeling, and machine learning .

Posted 10/8/2026full-timeRemote • United StatesLead💰 $131,000 - $178,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in advanced analytics, statistical modeling, and machine learning to drive business insights and decision-making. Proficient in developing scalable analytics solutions and communicating complex findings to diverse stakeholders.

Highest-signal resume keywords

Machine Learning Model DevelopmentStatistical Modeling TechniquesData Mining and Relationship AnalysisEnd-to-End Machine Learning PipelinesAgile Software Development Practices

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Quantitative AnalysisPredictive ModelingCausal InferenceAnomaly DetectionClusteringTime-Series ForecastingData Processing PipelinesStatistical InferenceDecision SystemsPattern Recognition

Soft Skills

Technical LeadershipMentorshipCommunication

Tools & Technologies

Cloud-Based Analytics EnvironmentLakehouse-Style Data ArchitecturesDistributed Data Processing Frameworks

Industry Keywords

Advanced AnalyticsBusiness Impact MeasurementData QualitySchema ManagementGovernance Controls

Tech Stack

Tools & technologies

Cloud

About the role

Key responsibilities & impact

Lead advanced analytics initiatives to solve complex business problems using quantitative analysis, statistical modeling, and machine learning
Design, develop, and deploy machine learning models for decision systems, recommendation and next-best-action frameworks, anomaly detection, pattern recognition, and forecasting/time series analysis
Liaise with business stakeholders and industrialize and monetize insights from advanced analytics projects
Research, implement, and validate causal inference, impact measurement, predictive modeling, clustering, and optimization methods
Analyze large, diverse datasets using statistical inference and data mining techniques to identify relationships, trends, and performance drivers
Develop and support scalable end-to-end analytics and machine learning solutions, data processing pipelines, and model lifecycle management practices
Support batch and near real-time/streaming data processing in a cloud-based analytics environment
Design and maintain lakehouse-style data platform architectures, including data quality, schema management, and governance controls
Use sampling methods and experimental or quasi-experimental approaches for research, analysis, and decision making
Translate analytical results and model insights into clear business language and communicate findings to technical and non-technical stakeholders
Lead requirements analysis, assess interdependencies and priorities, and align initiatives with strategic roadmaps and organizational goals
Apply Agile software development practices to analytics solutions
Provide technical leadership and mentorship to less experienced engineers or analysts

Requirements

What you’ll need

Master’s degree in Computer or Data Science, Business or Data Analytics, Information Technology or related field and 3 years of experience as a Data Scientist, Data Analyst, IT Consultant or related position
Alternatively, Bachelor’s degree in Computer or Data Science, Business or Data Analytics, Information Technology or related field and 5 years of experience as a Data Scientist, Data Analyst, IT Consultant or related position
Experience with advanced analytics and quantitative problem solving
Experience with statistical modeling and statistical inference techniques
Experience developing machine learning models
Experience with decision systems and recommendation/next-best-action frameworks
Experience with anomaly detection and pattern recognition
Experience with predictive modeling, clustering, and time-series forecasting analysis
Experience with causal inference and business impact measurement methods
Experience with data mining and relationship analysis on large datasets
Experience with end-to-end machine learning pipelines and model lifecycle management
Experience with scalable data processing using distributed data processing frameworks
Experience with batch and near real-time/streaming data processing
Experience with modern data platform architectures, including lakehouse-style data architectures
Experience with Agile software development practices and technical leadership

Benefits

Comp & perks

Equal employment opportunity policy
Remote/off-site work arrangement
No relocation required/relocation not eligible