Lead Data Scientist

Key Skills

Apache Hadoop, C Programming, C++, Data science techniques, Java Programming, Machine learning techniques, MapReduce, Python Programming, PyTorch, R Programming, Scala Programming, SQL, TensorFlow

Job Description

Caterpillar’s Large Power Systems Division (LPSD) designs and manufactures diesel and gas engines, ranging from 400 kilowatts to 16 megawatts of power, and the key engine systems such as fuel, air, after treatment and cooling which are used to power oil & gas, electric power, marine, rail and Cat machine applications around the world.

The LPSD Analytics team uses product domain knowledge including simulations, and advanced analytics methods such as, data mining, rule-based modeling, machine learning, anomaly detection, digital twin modeling and advanced statistical techniques to solve problems. The Lead Data Scientist contributes to this mission by acting as the technical lead of analytics project teams tasked with solving problems of medium to high complexity and may also be viewed as a technical expert in particular analytics approach, related digital technology, or business domain.

LPSD Analytics currently has an opening for a Lead Data Scientist. This position is located at our Mossville Tech Center - L facility. In this role, you will work on projects to invent and develop analytics solutions for moderate to highly complex technical problems related to engine systems. This position focuses on working with multiple digital groups within Caterpillar, including LPSD Analytics, ICS Analytics, Cat Digital, and Commercial Digital teams. What sets LPSD Analytics apart among the many digital teams is its engine domain knowledge and ability to effectively work together with the engine product group.

The successful candidate should have demonstrated analytical expertise, and firsthand experience designing, implementing, and deploying Machine Learning models for prognostics.

Significant challenges of this position include working in a rapidly growing field, where being a continuous learner in the analytics space is a must. The incumbent must quickly research new areas of analytics techniques and algorithmic approaches needed for meeting customer requirements, with the ability to work in Agile or digital NPI processes.

JOB DUTIES:

Caterpillar’s LPSD Analytics team uses quantitative techniques to solve problems for internal and external Caterpillar customers. Typical problems include modeling engine component or system behavior utilizing analytics techniques to diagnose and/or prognose product health (maintenance, failure). 

The principal responsibility of the Lead Data Scientist is to be the technical lead on analytics projects of medium to high complexity. The Lead Data Scientist is viewed as one of the most experienced technical experts in the organization whose breadth of knowledge in analytic techniques may be called upon to help on a multitude of business problems.

One of the key projects the Lead Data Scientist will work on during the first year involves the development of predictive engine component failure models, utilizing labelled 1-Hz time series data as well as daily engine codes (events and diagnostics) and meta data from assets with 4 years of running history. 

The Lead Data Scientist will:

• Demonstrate a breadth and depth of knowledge in the application of statistical and/or digital methods to solve product problems.
• Demonstrate competency in coaching and mentoring Analytics Developers in the creation, validation, and application of statistical models as well as in implementing digital solutions.
• Participate on 3-4 projects concurrently.
• Demonstrate strong initiative to research and apply new methods and digital technologies to exceed customer expectations.
• Have a strong focus on continual learning in the Analytics field.
• Demonstrate strong customer focus in the application of Analytics techniques and digital technologies to solve business problems.
• Demonstrate significant knowledge in the use of Data Analytics software solutions.

The Lead Data Scientist bears primary responsibility for solving the business problem presented through applied analytics. In addition, the Lead Data Scientist may be identified as an expert in a particular analytic approach, associated digital technology, or in the application of analytics in a particular business domain.

The Lead Data Scientist demonstrates thorough statistical and/or digital technology knowledge as well as the ability to solve complex problems. He or she demonstrates very good communication skills and the ability to explain conclusions to customers with limited knowledge and experience with quantitative analytical methods. Candidates for this position will be expected to have previous experience as the technical lead on project teams, and should exhibit strong communication skills, a penchant for innovation, and above average initiative, people development, and interpersonal skills. He or she should also have or be able to quickly acquire a comprehensive knowledge of Caterpillar Inc.; its products and services; its internal systems, processes, and procedures; and a general understanding of Caterpillar’s external customers, competitors, and market influencers.

BACKGROUND/EXPERIENCE:

Basic Qualifications:

• Bachelor’s degree in an accredited Engineering or Computer Science, Mathematics, Analytics, Data Science or related curriculum
• 10+ years of professional experience and at least 4 in analytics (7-9 years for those with Masters Degrees in analytics related field, 4-6 years for those with PhD in analytics related field)
• 4+ years of experience working in the field of machine analytics
• 2+ years of experience working directly with Machine Learning / Deep Learning techniques

Top Candidates Will Also Have:

• Excellent communication skills
• Advanced degree in Engineering or Computer Science, Analytics, Data Science or related field
• Prognostic analytics modeling experience
• Experience communicating complex concepts with clarity to lesser experienced audience
• Some experience with Condition Based Monitoring
• Experience working with time series data analysis
• Programming experience in Python, R, or SQL
• Ability to coach, develop and mentor team members