Principal Data Scientist

Oshkosh Corporation•Frederick, MD

2d•$118,700 - $211,300

About The Position

The Data Scientist responsibilities include conducting all the steps of the data mining lifecycle with an emphasis on applying their expertise in math, statistics and building machine learning models. They will follow the CRISP-DM methodology. Critical thinking and problem-solving skills are essential, along with a passion for research. Their role will include mentoring other members of the Advanced Analytics & Insights team. They will be responsible for preparing and delivering the results of their analysis. The goal will be to help our company utilize data analytics to generate business value.

Requirements

Master’s degree in Mathematics, Economics, Computer Science, Information Management, Statistics, Engineering or relevant field.
Proven experience as a Data Scientist with at least five years’ experience working in the field of data science
Strong math skills (e.g. statistics, algebra) and experience using statistical packages for analyzing datasets (Python, R)
Knowledge of and experience with data mining, segmentation, machine learning and optimization techniques.
Strong analytical skills with the ability to collect, organize, analyze, and disseminate significant amounts of information with attention to detail and accuracy.
Knowledge of and experience with data visualization and reporting packages (Cognos Analytics, Power BI, Tableau etc.)
Knowledge of and experience with Big Data databases (Azure, AWS, Oracle, NoSQL, etc.).
Aptitude for working in a fast-paced collaborative team environment with proven experience as a self-starter and problem-solver.
Excellent interpersonal skills as well as the ability to effectively present information and respond to questions from leaders and peers.

Nice To Haves

Experience within supply chain in automotive industry
Blockchain in supply chain management
Natural Language Processing
Deep learning

Responsibilities

Acquire business understanding and provide guidance and design input for model implementation.
Identify valuable data sources and automate collection processes.
Undertake preprocessing of structured and unstructured data.
Analyze large amounts of information to discover trends and patterns.
Build machine learning models and operation optimization (e.g., scheduling, routing, sales optimization).
Propose solutions and strategies for business value generation.
Collaborate with team members within segments and all functional areas, including sales, operations, supply chain, engineering, product development, finance, HR, etc.
Be a thought leader and stay up-to-date in the field of applied data science.