R&D Applied Data Scientist IV

The R&D Applied Data Scientist IV role employs statistical analysis, advanced machine learning techniques, and uses engineering principles and experience to inform and develop descriptive, diagnostic, and predictive analytics and algorithms based on large time-series data collected by various railroad wayside detectors.

Responsibilities: (Essential Functions)

1.

Broadly responsible for all aspects of the data life cycle with a strong emphasis on feature engineering, model development, validation and productization.
2.

Collaborate with engineering teammates to define data collection methods and specifications.
3.

Prepare large datasets for analysis through data cleaning and manipulation.
4.

Perform statistical analysis and machine learning to enhance system accuracy, improve defect detection, and predict defects.
5.

Design and develop end-to-end analytical pipelines, encompassing everything from foundational engineering principles, hardware integration, and algorithm development to validation, deployment, and ongoing optimization in production environments.
6.

Communicate insights using data visualization tools and techniques.
7.

Consult with Software Engineers to design or improve algorithms used in embedded products.
8.

All other duties as assigned.

Experience, Education, & License Requirements: 

• Bachelor’s degree in Engineering, Computer Science, Data Science, or Applied Mathematics, or Applied Physics required.
• Master’s Degree in related field preferred.
• 6+ years of experience in Data Science required.
• 1-3 years of additional experience in engineering preferred.
• Experience with time-series data required.

Skills & Abilities: 

• Proficiency in statistical analysis, machine learning, and signal processing techniques.
• Proficiency in numerical analysis tools/languages (MATLAB or R) and/or proficiency in Python and related data analysis libraries.

(NumPy, SciPy, etc.)
• Proficiency in at least one ML framework.

(PyTorch, TensorFlow, Theano, etc.)
• Strong foundation in the physics of dynamic motion and mechanical systems.
• Ability to correlate physical phenomena with data signatures and patterns.
• Working knowledge of SQL.
• Working knowledge of data engineering concepts.
• Familiarity with inertial sensors.

(force, acceleration, tilt, etc.)
• Familiarity with Linux commands and navigation.
• Ability to understand customer needs and requirements and to identify market opportunities through data analysis.
• Strong verbal and written communication skills.
• Able to work self-directed, independently and as part of a cross-functional team.

Competencies: 

• Organizing.
• Planning.
• Problem Solving.
• Peer Relationships.
• Patience.
• Adaptability/Flexibility.
• Creativity.
• Self-knowledge.
• Informing.

Education

Preferred


* Bachelors or better in Applied Mathematics


* Bachelors or better in Engineering


* Bachelors or better in Computer Science

Equa...