Senior Data Scientist

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Cummins Inc.

WebsiteLinkedInAll Job Openings

10,000+ employees

Founded 1919

⚡ Energy

🚗 Transport

🔧 Hardware

💰 $75M Grant on 2024-07

Energy • Transport • Hardware

Cummins Inc. is a global power technology leader that designs, manufactures, and distributes a variety of engines and power systems solutions. They offer products that range from diesel and natural gas engines to hybrid and electric power systems, as well as components like turbochargers, fuel systems, and emissions solutions. With a strong emphasis on innovation, Cummins aims to reduce emissions and improve fuel efficiency. The company is dedicated to helping industries navigate the transition to cleaner energy through integrated power solutions suitable for diverse applications such as on-highway, marine, mining, and construction. Additionally, Cummins provides services including remote monitoring, diagnostics, and aftermarket support, reinforcing its commitment to sustainability and customer service excellence.

📋 Description

• Research, design, implement and validate complex algorithms to analyze diverse sources of data to achieve targeted outcomes by leveraging complex statistical and predictive modeling concepts. • Leverage advanced analytics and data science to resolve complex analytical problems using quantitative approaches through a combination of analytical, mathematical and technical skills. • Build analytical machine learning solutions that predict and influence customer operating experience. • Partner with domain experts to verify model capabilities and with IT resources to enable appropriate data flow/data model development using appropriate tools/technology, rapid prototyping and inform the design of analytical products. • Identify relationships with patterns in data by using a suite of data exploration and data visualization techniques using tools such as PowerBI, R Shiny, SAS JMP and extracts insights into multivariate data by applying principles of multivariate data mining, small sample statistical inferential tests, dimension reduction techniques to understand the underlying structure of the data and enable sound conclusions upon model building. • Synthesize current business intelligence or trend data to support recommendations for action. • Develop applications for a Cloud-based environment and data extraction tools from a variety of sources using experience with Big Data technologies including SQL query language, Java, Python and C++. • Collect business intelligence data from available industry reports, public information, field reports, or purchased sources. • Identify and analyze industry or geographic trends with business strategy implications. • Generate standard or custom reports summarizing business, financial, or economic data for review by executives, managers, clients, and other stakeholders. • Create business intelligence tools or systems, including design of related databases, spreadsheets, or outputs. • Conduct or coordinate tests to ensure that intelligence is consistent with defined needs. • Analyze complex automotive and commercial vehicle business systems, industry requirements and data regulations. • Process and manage large data sets for vehicle and engine systems. • Perform comprehensive Requirements Analysis to evaluate relationships and interdependencies between requirements based upon their complexity and value to the business in order to determine feasibility and prioritization. • Utilize Agile software development methodologies to manage projects such as software development and advanced analytics product development to increase productivity and deliver products that meet value to customers.

🎯 Requirements

• Master’s degree in Computer or Data Science, or related field and 3 years of experience as a Data Analyst or Scientist, or related position. • Alternatively, the employer will accept a Bachelor’s degree in Computer or Data Science, or related field and 5 years of experience as a Data Analyst or Scientist, or related position. • Experience to include: Statistical and predictive modeling concepts; Building analytical machine learning solutions; Data visualization techniques using tools such as PowerBI, R Shiny, SAS JMP; Multivariate data mining; Develop applications for a Cloud-based environment; Big Data technologies including SQL query language, Java, Python and C++; Analyze complex business systems, industry requirements and data regulations; Requirements Analysis; Agile software development methodologies.