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Data Scientist

Job in North Sioux City, Union County, South Dakota, 57049, USA
Listing for: Sterling Computers Corporation
Full Time position
Listed on 2026-08-22
Job specializations:
  • IT/Tech
    Data Analyst, Data Scientist, Data Engineering, Machine Learning/ ML Engineer
Salary/Wage Range or Industry Benchmark: 90000 - 140000 USD Yearly USD 90000.00 140000.00 YEAR
Job Description & How to Apply Below
Location: North Sioux City

If you are unable to complete this application due to a disability, contact this employer to ask for an accommodation or an alternative application process.

Data Scientist

Full Time North Sioux City, SD, US

Title
:
Data Scientist

Reports to
:
Director of Product and Business Development

Job Description
:
Sterling is seeking a highly skilled and motivated Data Scientist to join our growing team. In this role, you will be instrumental in developing and implementing advanced data solutions that enhance our operational and financial reporting capabilities. You will work on internal data science projects, build sophisticated data products, and provide data-driven insights to support our sales teams. Additionally, you will play a key role in our nascent generative AI initiatives, exploring and applying cutting-edge techniques to unlock new possibilities.

Primary Responsibilities

  • Design, develop, and deploy complex data products and models to improve operational efficiency and financial reporting accuracy.
  • Collaborate with cross-functional teams, including operations, finance, and sales, to understand business needs and translate them into data science solutions.
  • Perform in-depth data analysis to identify trends, patterns, and insights that can drive business improvements and inform strategic decisions.
  • Develop and maintain robust data pipelines and integrate various data sources to ensure data quality and accessibility.
  • Support sales teams by providing analytical tools, predictive models, and custom reports that enhance sales performance and customer understanding.
  • Participate in the research, experimentation, and implementation of generative AI models and applications, contributing to the company's innovative efforts.
  • Communicate complex analytical findings and recommendations clearly and effectively to technical and non-technical stakeholders.
  • Stay current with the latest advancements in data science, machine learning, and artificial intelligence.

Qualifications

  • Bachelor's or Master's degree in a quantitative field such as Computer Science, Statistics, Mathematics, or a related discipline. A Ph.D. is excellent.
  • Strong proficiency in Python is extremely important, including experience with libraries such as pandas, scikit-learn, and PyTorch.
  • Solid understanding and experience with data modeling principles.
  • Proficiency in SQL for data extraction and manipulation.
  • Experience with Databricks.
  • Ability to work alongside data engineers including building and maintaining data pipelines.
  • Proven ability to work effectively alongside data analysts and data engineers, fostering a collaborative environment.
  • Must enjoy working with both technical and non-technical coworkers to understand their problems and collaboratively create innovative data solutions.
  • Demonstrates boundless curiosity and creativity in approaching data challenges.

Preferred Experience:

  • Experience with agentic AI concepts or applications.
  • UI prototyping capabilities, particularly with tools like Streamlit.
  • R programming experience.

Sterling Computers Corporation (“Sterling”) is an Equal Opportunity Employer. Qualified applicants will receive consideration for employment without regard to age, race, color, creed, religion, disability, medical condition, economic status or status with regard to public assistance, citizenship status, national or social or ethnic origin, past or present membership in the uniformed services, protected veteran status, sex, pregnancy, marital or civil union or domestic partnership status, family or parental status, sexual orientation, gender expression or identity, family medical history or genetic information, HIV status, political belief, or any other status or characteristic protected by applicable law.

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