Data Scientist

Sterling

North Sioux City (SD)

On-site

USD 110,000 - 160,000

Full time

14 days+
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Job summary

Sterling is seeking a highly skilled Data Scientist to design, build, and deploy advanced data products and models that improve operational efficiency and financial reporting. You will work with operations, finance, and sales to translate business needs into data-driven solutions and support our growing generative AI initiatives.

You will develop data pipelines, apply modern ML techniques, and communicate insights to stakeholders.

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.

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 translate business needs into data science solutions.
  • Perform in-depth data analysis to identify trends and insights that drive business improvements.
  • Develop and maintain robust data pipelines and integrate data sources to ensure quality and accessibility.
  • Support sales teams by providing analytical tools, predictive models, and custom reports.
  • Participate in research and implementation of generative AI models and applications.
  • Communicate complex analytical findings clearly to technical and non-technical stakeholders.
  • Stay current with advancements in data science, machine learning, and AI.

Skills

Python programming
Data analysis
Cross-functional collaboration
Curiosity and creativity

Education

Bachelor's or Master's in CS/Statistics/Mathematics

Tools

Pandas
Scikit-learn
PyTorch
SQL
Databricks
Streamlit

Job description

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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