ROOTLOGIK Background:

ROOTLOGIK is a business solutions supplier to General Motors. We support several business groups and systems across the organization. We are currently looking for a Entry Level Data Scientist to supplement our team.

Key Responsibilities:

As a Entry Level Data Scientist for ROOTLOGIK, you will work on a wide range of data-driven initiatives that support both strategic and operational decisions for our clients. You will be responsible for cleaning, transforming, analyzing, and modeling data to uncover insights, solve complex problems, and help businesses make more informed decisions.

Interface with the client to represent the work being done by ROOTLOGIK
Collaborate closely with cross-functional teams to deliver impactful solutions using advanced analytics and machine learning technique
Develop a thorough understanding of the client’s business including business processes, applications and data which directly support running their business and help drive informed decisions
Develop, implement and/or support methods to collect, measure, merge, clean and analyze data from multiple sources
Develop various data models to support the business in predicting, identifying and/or root causing issues

A successful Junior Data Scientist will have:

Bachelor’s degree in data science, Computer Science, Statistics, Engineering, Mathematics, or a related quantitative discipline.
1–2 years of hands-on experience working with data—this may include internships, co-op programs, academic research, or personal projects with documented results.
Strong proficiency in Python for data manipulation, analysis, and machine learning. Hands-on experience with core libraries such as Pandas, NumPy, and Scikit-learn is required.
Strong knowledge of statistics and applied machine learning, including supervised and unsupervised learning techniques such as regression, classification, clustering, SVM, KNN, and basic NLP.
Experience with SQL for querying, joining, and analyzing data from relational databases.
Familiarity with cloud computing platforms, especially AWS, including tools such as S3, EC2, or SageMaker for data storage and model deployment.
Basic understanding of data engineering concepts, such as ETL pipelines or API integration.
An ability to interpret complex datasets, uncover trends, and effectively communicate data-driven insights to both technical and non-technical audiences.
Ability to self-manage tasks, work independently and deliver effectively.
Analytical problem-solving skills that will allow them to define the problems, collect the necessary data, establish facts, and draw valid conclusions.

Nice-to-Have:

Experience with data visualization tools such as Tableau or Power BI
Familiarity with version control systems such as Git or GitHub for managing and collaborating on code.
Basic understanding of Large Language Models (LLMs) or Generative AI tools (OpenAI GPT, Hugging Face Transformers, LangChain)
Background or project experience in the automotive industry.

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