Data Scientist

STG Logistics - Tropicana/Naked Juice Div.; Kansas; Remote; USD 100,000 - 125,000; Part time

Job summary

A leading logistics company is seeking a Part-Time Data Scientist to join their remote Data & Analytics team. This role involves analyzing large datasets, building predictive models, and collaborating with various teams to enhance operational efficiency. Ideal candidates will have a strong background in data science and excellent communication skills to present findings effectively.

Benefits

Competitive hourly compensation

Opportunity to contribute to impactful projects

Collaborative, innovative team environment

Exposure to a growing, technology-driven logistics leader

Qualifications

• At least 2 years of experience in data science or analytics.
• Strong problem-solving skills and enthusiasm for data-driven solutions.
• Excellent communication skills to translate complex findings into actionable insights.

Responsibilities

• Analyze large datasets to extract insights and support strategic decisions.
• Build and validate predictive models and machine learning algorithms.
• Collaborate with cross-functional teams to identify automation opportunities.

Skills

Python

R

SQL

Data Visualization

Problem Solving

Education

Bachelor’s or Master’s degree in Data Science, Statistics, Computer Science, Mathematics

Tools

Tableau

Power BI

scikit-learn

TensorFlow

XGBoost

Job description

Job Title: Part-Time Data Scientist (Remote)

Company: STG Logistics

Location: Remote (U.S.-based preferred)

Job Type: Part-Time (15–25 hours/week)

Industry: Logistics & Supply Chain

About STG Logistics:

STG Logistics is a leading provider of logistics and transportation services, specializing in port-to-door solutions across North America. We leverage a strong network and advanced technology to deliver customized, scalable services that streamline operations and reduce costs. Our commitment to innovation and data-driven decision-making distinguishes us in the logistics industry.

Position Overview:

We are seeking a highly analytical and motivated Part-Time Data Scientist to join our Data & Analytics team. In this remote role, you will collaborate with cross-functional teams to develop predictive models, uncover insights, and enhance operational efficiency through advanced analytics. This position offers flexibility and an excellent opportunity to apply your skills in a dynamic industry.

Key Responsibilities:

1. Analyze large datasets to extract insights and support strategic decisions.
2. Build and validate predictive models and machine learning algorithms to optimize logistics operations (e.g., route efficiency, demand forecasting, capacity planning).
3. Collaborate with IT, operations, and business teams to identify automation and process improvement opportunities.
4. Create visualizations and present findings clearly to non-technical stakeholders.
5. Maintain data quality and integrity in all analytical outputs.
6. Stay informed on industry trends and emerging technologies in data science and logistics.

Required Qualifications:

1. Bachelor’s or Master’s degree in Data Science, Statistics, Computer Science, Mathematics, or a related field.
2. At least 2 years of experience in data science, analytics, or a similar quantitative role.
3. Proficiency in Python or R, SQL, and data visualization tools (e.g., Tableau, Power BI).
4. Experience with machine learning libraries (e.g., scikit-learn, TensorFlow, XGBoost).
5. Strong problem-solving skills and enthusiasm for data-driven solutions.
6. Excellent communication skills to translate complex findings into actionable insights.
7. Ability to work independently in a remote setting.

Preferred Qualifications:

1. Experience in logistics, supply chain, or transportation analytics.
2. Familiarity with cloud platforms such as AWS, Azure, or GCP.
3. Knowledge of optimization techniques and real-time data processing.

What We Offer:

1. Competitive hourly compensation.
2. Opportunity to contribute to impactful projects with real business value.
3. A collaborative, innovative team environment.
4. Exposure to a growing, technology-driven logistics leader.