Data Science Engineer - Part Time (Shreveport, LA)

Pratt Industries•Atlanta, LA

3d•Hybrid

About The Position

This part-time, entry-level position supports the data science initiatives within BRR Plus’s areas of responsibility, including Pratt Industries and Visy. The employee will work closely with Data Science Engineers to assist with data preparation, analysis, reporting, and the development of analytical and machine learning solutions. This role will help the team identify useful business insights and support operational improvement efforts across assigned areas.

Requirements

Currently pursuing, or recently completed, post-secondary education in data science, computer science, engineering, mathematics, statistics, information systems, or a related technical field.
High school diploma or equivalent is required.
Proficiency with Microsoft Word, PowerPoint, and Excel, including data organization, calculations, charts, and reporting.
Working knowledge of Python and common data analysis libraries or equivalent programming experience.
Ability to perform basic mathematical calculations, including addition, subtraction, multiplication, division, percentages, ratios, and averages.
Basic understanding of algebra, statistics, trends, and data interpretation.
Ability to apply mathematical concepts to assigned data analysis and operational support tasks.
Ability to use calculators, spreadsheets, or other approved analytical tools to perform and verify calculations.
Ability to identify basic problems, unusual results, missing information, and potential data-quality concerns.
Ability to organize information and use logical reasoning to support problem-solving activities.
Ability to interpret instructions provided in written, verbal, diagram, or schedule form.
Ability to execute established analytical workflows and make appropriate updates to existing scripts and tools.
Ability to recognize unexpected results, troubleshoot common issues, and clearly communicate findings or concerns.
Ability to maintain accuracy, consistency, and organization across data, code, reports, and project documentation.
Ability to read and understand instructions, procedures, technical documentation, and training materials.
Ability to communicate professionally with Data Science Engineers, employees, and other internal business partners.
Ability to ask questions, receive feedback, and communicate project progress, problems, and findings clearly.
Clear and concise verbal and written communication skills.

Nice To Haves

Coursework, personal projects, internships, or other experience involving data analysis, programming, statistics, or engineering applications is preferred.
Knowledge of DCS systems, Data Historians, and Data Analytics software such as: dataParc, Seeq, Python
Analytical mind and business acumen
Strong math skills (e.g. statistics, algebra)
Problem-solving aptitude
Excellent communication and presentation skills
Current enrollment in, or completion of, a college, university, technical school, vocational program, military technical program, or other relevant educational program is preferred.
Candidates are preferred who offer the following: Data Science, Chemical Engineering, Computer Science, Electrical Engineering, Mechanical Engineering, Pulp and Paper Science, Mathematics or Statistics, Information Systems, Industrial Engineering
Familiarity with Seeq, dataParc, process data historians, visualization platforms, and machine learning or artificial intelligence tools is preferred.

Responsibilities

Provide general project support to Data Science Engineers and other members of the data science team.
Gather, organize, clean, and validate data using established procedures and approved data sources.
Assist with routine analysis and help identify trends, unusual results, missing information, and data-quality concerns.
Make updates to existing reports, dashboards, scripts, and analytical tools.
Assist with testing data products and documenting results, issues, and recommended corrections.
Prepare charts, summaries, and visualizations for internal review and operational discussions.
Assist with tool demonstrations, user documentation, training preparation, and implementation support.
Complete assigned tasks accurately, maintain organized project documentation, and communicate progress or problems to the supervising Data Science Engineer.