Senior Data Scientist

Role Definition
Assists in the design, definition, development, and test of the robotics software development; collaborates with senior engineers to ensure that internal and external clients' needs are met.

Responsibilities

• Independently lead E2E Analytics projects. Act as a product owner and Coach the analysts within the team
• Work closely with business stakeholders to understand their goals & determine how Data analytics can be used to achieve those goals.
• Should be able to design data modelling processes, create algorithms & develop predictive models to help analyze the data
• Develop prediction tools which can help Caterpillar customers to gain efficiency and plan the forecast better
• Develop innovative solutions which enables machine learning and prediction. Also, Work with Cross - functional team to come up with innovative solutions
• Act as a Technical lead in the field of Analytics and Machine Learning.

Experience:

• Passionate Product Analytics Engineer with minimum 8+ years of experience in developing Data Analytics solutions, Visualization tools & ML algorithms etc.

Education:

• B.Tech/M.Tech (preferably Mechanical) or equivalent professional qualification in Data Science, Statistics, Machine Learning for Engineering Components

Skill Descriptors

• Industry Knowledge:
• Has a good understanding of off-highway products.
• Has worked as a part of product development team or validation teams
• Basics of Engine/Machine performance parameters, Specifications, Data Links.
• Ability to relate Machine problems and come up with analytical solutions Programming:
• High skilled in Python, SQL, SAS, AI/ML Tools, Neural network development
• Strong knowledge in python, SQL
• Fully skilled in Visualization tools such as Power Bi, Tableau with ability to utilize it as Automation tool
• Should have experience in building algorithms
• Should have experience in developing prediction formulas for non-linear data.
• Self starter & passionate for Data analysis
• Can make use of statistical tools for data prediction.
• Regression analysis (Linear/Non-linear)
• Should be able to present the data in a meaningful form
• Passion for Innovation and Technology
• Self-Starter, should be able to present Ideas to stakeholders
• Problem Solving: Knowledge of approaches, tools, techniques for recognizing, anticipating, and resolving organizational, operational or process problems; ability to apply knowledge of problem solving appropriately to diverse situations.
• Level Extensive Experience:
• Ensures capture of lessons to be learned from a problem-solving effort.
• Organizes potential problem solvers and leads problem resolution efforts.
• Uses varying problem-solving approaches and techniques as appropriate.
• Contributes to standard practices for problem-solving approaches, tools, and processes.
• Analyzes and synthesizes information and devises alternative resolution strategies.
• Develops successful resolutions to critical or wide-impact problems.