Junior Data Scientist

About Zeigler:

Zeigler Automotive Group is one of the largest privately-owned dealer groups in the U.S. with 78 franchises across 35 locations in Wisconsin, Illinois, Indiana, and Michigan. Vehicle brands represented include Toyota, Hyundai, Chevrolet, Fiat, Honda, Ram, Ford, Lincoln, Chrysler, Dodge, Jeep, Maserati, Alfa Romeo, Nissan, Infiniti, Cadillac, Buick, GMC, Subaru, BMW, Mercedes Benz, Sprinter, Jaguar, and Land Rover.

Besides its extensive automotive portfolio, the organization owns and operates Zeigler Motorsports, an 85,000-square-foot motorsports dealership and action park, offering 19 different powersports brands, plus its own onsite restaurant: Trak Houz Bar & Grill. Additionally, Zeigler Motorsports houses the Elevate Leadership & Team Building Academy, an executive training company.

We are eager to find a candidate with the passion, experience, and ability to lead significant R&D tasks and product evolution, either independently or with a virtual engineering team.

Regarding the Job:

In your role as a Data Science Associate, you will use AI, ML (Machine Learning) to provide actionable intelligence and predictive solutions to our team in order to develop innovative product solutions. You will gain experience working in Augmented Reality (AR), Machine Learning (ML), Natural Language Processing (NLP), and developing data-driven solutions to construct algorithms while working closely with other members of our Data Science and engineering team to contribute to the evolution of our product. In addition to assisting our data science model creation and data teams, you will assist the product team in identifying development opportunities. You over-invest in the visual and interaction and have a passion for solving problems while developing patentable innovations.

Required Abilities:

Collaborate with Product Managers and Engineers to examine data and the user experience in depth.

Construct product metrics and statistical models to identify expansion prospects.

Handle data annotation and data analysis requests from multiple stakeholders in a fast-paced environment with high efficiency and quality.

Contribute to the development of the annotation standards.

Analyze and evaluate language data trends and patterns.

Participate in the testing and induction of an annotation tool.

Monitor and report on quality metrics and ensure delivery of all KPIs and SLAs agreed upon with stakeholders.

Maximize productivity, process efficiency, and quality via workflow simplification, process standardization, documentation, audits, and periodic investigations.

Qualifications:

Bachelor's degree or its equivalent in Mathematics, Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or a related field; or related work experience.

One or more years of experience as a data scientist, modeling in Python or R is required.

Students pursuing bachelor's or master's degrees in data science, statistics, applied mathematics, computer science, engineering, or other quantitative disciplines that provide adequate data science foundations.

Exposure to coding (Python preferred, R and SQL acceptable), collaboration (Git), developing models (machine learning, boosting & bagging algorithms, &/or regression techniques), and conducting predictive analytics testing and evaluation (match case analysis, confidence intervals, experimental design, etc.).

A desire to study and tackle difficult problems.