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Part Time Data Science Jobs in Plano, TX (NOW HIRING)

IQVIA

MedTech

Dallas, TX · On-site

$36 - $38/hr

We believe in pushing the boundaries of human science and data science to make the biggest impact ... part-time). Dependent on the position offered, incentive plans, bonuses, and/or other forms of ...

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Part Time Data Science information

What is a part-time data science job?

A part-time data science job involves working fewer hours than a full-time data scientist, typically less than 40 hours per week. Part-time data scientists perform many of the same tasks as their full-time counterparts, such as analyzing data, building models, and generating insights to help organizations make data-driven decisions. These roles are ideal for students, professionals seeking additional income, or those looking for flexible work arrangements. Part-time positions may be project-based or ongoing, and can be found in various industries including tech, healthcare, finance, and retail.

What are part-time data science jobs?

Part-time data science jobs focus on the collection, analysis, and manipulation of data sets. In this role, you can either work for one employer or freelance on a per-project basis. As a data scientist or data analyst, you mine and analyze information. Your duties also include using statistics and math on the data sets to develop algorithms and models that perform specific processes or aid with your employer’s decision-making. Machine learning engineers use data to create algorithms that help computers and machines process information in structured and unstructured environments and make decisions or take actions based on the data.

What are the key skills and qualifications needed to thrive as a part-time data scientist, and why are they important?

To thrive as a Part Time Data Scientist, you need strong analytical skills, statistical knowledge, and proficiency in programming languages like Python or R, often supported by a degree in a quantitative field. Familiarity with data analysis tools, machine learning libraries, and platforms such as SQL, Jupyter, or Tableau is typically required. Effective communication, time management, and problem-solving abilities help you deliver impactful insights within limited hours. These skills ensure you can efficiently analyze data, present findings clearly, and drive value for organizations even with part-time commitment.

How do part-time data science roles typically structure team collaboration and project ownership?

In part-time data science positions, collaboration is often facilitated through regular virtual meetings, shared project management tools, and clear documentation. Part-time data scientists usually work on specific projects or components, such as data cleaning, exploratory analysis, or building models, while maintaining close communication with full-time team members and stakeholders. This structure allows for flexibility but also requires strong self-management and proactive updates to ensure alignment with the broader team's objectives. Many organizations use agile methodologies to assign tasks and track progress, making it easier for part-time contributors to integrate their work seamlessly.
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What are the most commonly searched types of Data Science jobs in Plano, TX?

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What cities near Plano, TX are hiring for Part Time Data Science jobs?

Cities near Plano, TX with the most Part Time Data Science job openings:

Part Time Data Science jobs near you
Infographic showing various Part Time Data Science job openings in Plano, TX as of August 2026, with employment types broken down into 1% As Needed, 88% Full Time, 9% Part Time, and 2% Contract. Highlights an 84% Physical, 4% Hybrid, and 12% Remote job distribution.

Manager, Simulation Engineering (R4870)

Shield AI

Dallas, TX

Full-time, Part-time

Re-posted 8 days ago

Job description

Shield AI is a venture-backed defense-tech company with the mission of protecting service members and civilians with intelligent systems. Its products include Hivemind autonomy software, V-BAT and X-BAT aircraft, and Aechelon simulation and synthetic reality technologies. With offices and facilities across the U.S., Europe, the Middle East, and Asia-Pacific, Shield AI’s technology actively supports operations worldwide. For more information, visit www.shield.ai. Follow Shield AI on LinkedIn, X, Instagram, and YouTube. 

Job Description:
As the VBAT Simulation Lead, you will be responsible for improving and scaling our simulation capabilities for the V-BAT and future aircraft. You will design, resource, manage, build and integrate tooling across our various engineering teams (e.g. Aerodynamics, GNC, Propulsion, etc.) to enable efficient and scalable simulation workflows. Your simulation solutions will be a key development tool for other engineers and also a critical gate in our release process. 
What you'll do:
  • Work with tech leads and stockholders to design,  track, and report simulation roadmaps and release plans.  
  • Align needs and priorities across many teams and disciplines 
  • Hire and manage a team of specialized simulation engineers across multiple locations. 
  • Collaborate with cross-functional teams, including software engineers, autonomy engineers, and aerodynamics engineers, to ensure the simulation accurately reflects real-world conditions 
  • Create and maintain processes and workflows to build confidence in simulation tooling to both internal and external customers.  
  • Stay updated with the latest advancements in simulation technologies and drive best practices across the team 
  • Build and maintain documentation and dashboards to quickly provide data and status to leadership. 
Required qualifications:
  • BS in Computer Science or related engineering field with 8+ years of professional experience. 
  • 3+ years of experience leading engineering teams or projects. 
  • Passion for simulation and testing with the goal of ensuring safety and reliability at scale. 
  • A proven track record of working with multiple stakeholder groups and managing clear and successful roadmaps 
  • Strong foundation in C++ and software architecture  
  • Foundational knowledge of statistics and its application in software development, testing, and data analysis.  
  • Solid understanding of mathematics (especially linear algebra) and foundational physics, with the ability to interpret technical papers and algorithms effectively.
Preferred qualifications:
  • Experience with Docker, Kubernetes, and/or containerized application development 
  • Familiarity with rigid body dynamics (e.g. Euler’s equations, quaternions), aerodynamics, propulsion systems, etc.  
  • Experience with Python 3 and data science frameworks (e.g. NumPy, Pandas, Dagster)  
  • Experience with robotics concepts, including node-based architectures such as ROS or similar middleware frameworks. 
#LI-SM1
#LD

Full-time regular employee offer package:
Pay within range listed + Bonus + Benefits + Equity
 
Temporary employee offer package:
Pay within range listed above + temporary benefits package (applicable after 60 days of employment)
 
Salary compensation is influenced by a wide array of factors including but not limited to skill set, level of experience, licenses and certifications, and specific work location. All offers are contingent on a cleared background and possible reference check. Military fellows and part-time employees are not eligible for benefits. Please speak to your talent acquisition representative for more information.
 
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Shield AI is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, marital status, disability, gender identity or Veteran status. If you have a disability or special need that requires accommodation, please let us know. 

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.