Data Scientist

The Data Scientist solves analytical and business problems using quantitative, statistical, mathematical, and technical approaches. This role researches, designs, implements, and validates algorithms to analyze diverse data sources and generate actionable insights. The Data Scientist applies statistical and predictive modeling techniques to support business decisions, improve processes, and deliver project-specific outcomes.

Key Responsibilities

• Apply data science methodologies to solve complex business problems and generate data-driven insights.
• Research, design, develop, implement, and validate statistical and predictive models and algorithms.
• Develop algorithms using statistical methodologies, programming languages, and data science tools.
• Clean, prepare, profile, and transform data to ensure quality and suitability for analysis and modeling.
• Perform data mining, exploratory analysis, and data visualization to identify relationships, patterns, trends, and anomalies.
• Develop and evaluate statistical and machine learning models for regression, classification, forecasting, anomaly detection, and other business applications.
• Partner with domain experts and cross-functional stakeholders to validate model capabilities, assumptions, and business relevance.
• Analyze complex requirements and data to determine appropriate analytical approaches, feasibility, and priorities.
• Clearly communicate analytical results, methodologies, assumptions, and recommendations to technical and non-technical stakeholders.
• Develop robust, data-based solutions and support systematic problem solving and root-cause analysis.
• Apply appropriate validation, testing, quality control, and model evaluation techniques to ensure reliable analytical solutions.
• Leverage emerging data science, digital, cloud, and technology solutions to continuously improve analytical capabilities.
• Contribute to the continuous development of the team through knowledge sharing, collaboration, and mentoring.
• Follow applicable business, technical, security, governance, compliance, and data regulations while developing and implementing solutions.

Skills And Experience

• Experience or strong knowledge of data science, statistical analysis, predictive analytics, and machine learning concepts.
• Experience processing, managing, and analyzing large and complex datasets.
• Knowledge of big data technologies, open-source platforms, and third-party data science toolsets.
• Experience developing analytical solutions to address business and operational problems.
• Proficiency in SQL and experience working with structured and unstructured data.
• Knowledge of statistical modeling techniques, including regression, classification, time-series analysis, anomaly/outlier detection, probability distributions, and hypothesis testing.
• Programming experience with statistical or data science programming languages and tools.
• Experience with data mining, data exploration, visualization, feature selection, data transformation, imputation, resampling, and model quality-control techniques.
• Familiarity with cloud-based and clustered computing environments, preferably Microsoft Azure and/or Amazon Web Services.
• Experience implementing or supporting Big Data platform solutions using open-source and third-party technologies.
• Familiarity with machine learning model validation, testing, and performance evaluation.
• Familiarity with Agile software development methodologies and practices.
• Knowledge of Continuous Integration and Continuous Delivery (CI/CD) concepts is preferred.
• Ability to analyze complex business systems, industry requirements, and applicable data regulations.
• Strong problem-solving and analytical thinking skills, with the ability to identify root causes and develop sustainable solutions.
• Strong communication skills, with the ability to present complex analytical concepts and findings clearly to different audiences.
• Customer-focused approach with the ability to build effective relationships and deliver solutions aligned with business needs.
• Ability to make sound, timely decisions using data and analytical evidence.
• Ability to manage complex, high-volume, and sometimes contradictory information.
• Technology-savvy mindset with an interest in adopting emerging digital and data science technologies.
• Ability to collaborate effectively with diverse teams, stakeholders, and subject matter experts and value different perspectives.

Qualifications

• College, university, or equivalent degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, Information Technology, or another relevant technical discipline, or equivalent relevant experience.
• Relevant internship, co-op, temporary student employment, academic projects, or extracurricular team experience is preferred.

Job Systems/Information Technology

Organization Cummins Inc.

Role Category On-site with Flexibility

Job Type Exempt - Experienced

ReqID 2435057

Relocation Package No

100% On-Site No