Senior Data Scientist

Position Summary: 

As a Senior Data Scientist, you will drive the development and implementation of Machine Learning and Artificial intelligent techniques for Penske next-generation Supply Chain & Logistics products. With a robust background in data science and industry experience with machine learning, coding, and distributed computing systems such as PySpark, your role will be instrumental in establishing and advancing Penske's predictive analytics capabilities, particularly at the enterprise level.

In addition to your hands-on contributions, you will serve as a mentor to less experienced data scientists, guiding them towards professional growth and instilling a culture of best practices within the team. As a Senior Data Scientist, you will simultaneously navigate multiple projects, each of significant scale and complexity, with potential organization-wide impact. You will be expected to provide detailed analysis, formulate project approaches, and define their scope. Success in this role involves extensive cross-functional collaboration with customers, vendors, and suppliers.

Major Responsibilities:

Strategic Opportunities and Process Improvement:

• Collaborate closely with diverse stakeholders to identify and define complex business problems

• Conduct comprehensive ROI analysis to establish the feasibility of potential projects

• Contribute to building business cases for significant, enterprise-wide analytics initiatives

Data Evaluation and Analysis:

• Identify appropriate data sources to answer intricate business questions

• Extract, blend, cleanse, and organize data, leveraging automated ETL processes

• Visualize data to facilitate understanding and decision-making

• Identify and address outliers, missing or incomplete records in the data

Model Building and Implementation:

• Identify appropriate techniques and algorithms for model construction

• Develop, test, and fine-tune machine learning models

• Construct applications and embed models for enterprise-level use

Communication and Leadership:

• Actively engage in best practices discussions with team members regarding modeling activities

• Provide regular updates on project activities and results with the team

• Participate in and lead discussions about Penske's data-driven vision and strategy

• Act as a mentor for junior data scientists, fostering their growth and development

Exploring New Technologies and Industry Trends:

• Stay abreast of business trends in the logistics industry

• Evaluate new technologies and assess their potential application to our business

Qualifications for External Candidates  

 

 

Qualifications:

• 6+ years of experience along with a master’s degree in Engineering, Operations Research, Statistics, Applied Math, Computer Science, or related quantitative field required

• 4+ years of experience along with a PhD in Engineering, Operations Research, Statistics, Applied Math, Computer Science, or related quantitative field preferred.

• Minimum of 4 years of experience designing and building machine learning applications using both structured and unstructured datasets.

• Demonstrated proficiency in Python, or other high-level scripting languages, with practical experience in programming.

• Extensive experience in distributed computing frameworks, such as PySpark, is required

• Proven expertise in the application of advanced Machine Learning and Deep Learning techniques in a business environment is a must.

• Solid experience with SQL.

• Ability to manage multiple complex projects simultaneously

• Experience translating complex data insights into strategic recommendations for non-technical stakeholders.

• Strong oral and written communication skills

• Strong ability to collaborate with different functional teams and stakeholders with both tech and non-tech backgrounds. 

• Demonstrated ability to mentor and guide junior team members.

• Familiarity with model deployment, MLOps practices as well as exposure to containerization technologies (like Docker) and orchestration systems (like Kuberne