Senior Data Scientist

Payrate: $52.00 - $56.00/hr. Summary: The Machine Data Insights team within Machine Analytics is seeking a talented and motivated Data Scientist to develop analyses that support product development analytics, aftermarket analytics, demand forecasting analytics, and other strategic analytics areas of focus. Our team’s mission is to understand our customers where their work gets done. Our analyses reveal machine usage insights that help our customers work safer and more productively and help our enterprise understand the market trends that shape our future business. This role will require a skillset in advanced statistical modeling and machine learning techniques as well as domain knowledge of industrial equipment. Responsibilities: • The Data Scientist I will participate on cross-functional project teams in order to solve a problem presented by a Company Business Unit or Service Organization, a Company Dealer, or a Company Customer. • The key role of this second level data scientist position is to move from learning and assisting others to learning to contribute independently. • The Data Scientist I is expected to become familiar with the company’s processes, products, and organization. • Work is typically directed by a project or team lead who might review both methods and results. • Challenges include meeting expectations in delivering results, learning to consider alternative courses of actions, making timely decisions, developing communication skills, working with people, and pushing the technical bounds of experimentation while meeting customer commitments. • Individuals in this position might expect to have several assignments allowing them to gain experience on multiple projects. • They will be expected to apply theory and concept in contributing to the solution in the assigned area. • The job function may include data collection and analysis; development, validation, application, and refinement of statistical models; application of related digital technologies in processing both the inputs and outputs from the models. Qualifications: • Typically requires a Bachelor’s degree, preferably in engineering, computer science, statistics, economics, mathematics, or a similar field with quantitative coursework, and 1-2 years of professional experience utilizing quantitative analysis is required, or a Master’s or PhD degree. • Must be comfortable working in industry standard statistics, analytics, and data visualization packages. • Must demonstrate strong initiative, interpersonal skills, and the ability to communicate effectively. Preferred Qualifications: • Bachelors, Masters, or PhD degree in Applied Statistics, Data Science, Business Analytics, Business Intelligence & Analytics, Computer Science, Computer Science + X, Engineering (Aerospace, Electrical, Mechanical, Computer, Industrial, Agricultural, etc.), Informatics, Information Systems Management, Mathematics, MBA with Technical Undergrad, Predictive Analytics, Statistics, or equivalent technical degree. • Experience with advanced data analysis and statistical methods such as regression, hypothesis testing, ANOVA, statistical process control, etc. • Practical applications of machine learning techniques such as Clustering, Logistic Regression, CART, Random Forests, SVM or Neural Networks. • Experience in design / development of heavy equipment (ex. automotive, aerospace, engine, transmission, construction, mining, industrial, etc) • Strong technical and problem-solving skills and evidence of continuous learning in the analytics field • 2+ years of experience applying python (NumPy, SciPy, pandas, etc) programming to solve business challenges • Experience with cloud technologies (AWS, Azure, Google Cloud, etc) • Strong initiative to research and apply new methods and digital technologies to exceed customer expectations. • Good communication, interpersonal, and collaboration skills3-5 years experience. Desired Skills: • The data scientist I demonstrates an expanded breadth of knowledge and the ability to handle basic issues independently. • They also demonstrate very good communication skills; planning and organization, teamwork, and decision making skills. • A strong concern for customers; a strong focus on continual learning in the analytics field Pay Transparency: The typical base pay for this role across the U.S. is: $52.00 - $56.00/hr. Final offer amounts, within the base pay set forth above, are determined by factors including your relevant skills, education and experience and the benefits package you select. Full-time employees are eligible to select from different benefits packages. Packages may include medical, dental, and vision benefits, 10 paid days off, 401(k) plan participation, commuter benefits and life and disability insurance. 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