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Part Time Science Jobs in Draper, UT (NOW HIRING)

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Part Time Science information

See Draper, UT salary details

$22.9K

$45.2K

$73.9K

How much do part time science jobs pay per year?

As of Jul 30, 2026, the average yearly pay for part time science in Draper, UT is $45,238.00, according to ZipRecruiter salary data. Most workers in this role earn between $36,000.00 and $48,600.00 per year, depending on experience, location, and employer.

What are part-time science jobs?

Part-time science jobs are roles in scientific fields that require fewer hours than a standard full-time position, often offering flexible schedules. These jobs can include positions such as lab assistants, research technicians, science tutors, or teaching assistants, among others. They are ideal for students, professionals seeking work-life balance, or those looking to gain experience in science without committing to full-time hours. Responsibilities and requirements vary depending on the specific job and employer, but typically involve supporting scientific research, education, or laboratory operations.

What are the key skills and qualifications needed to thrive as a Part-Time Science Teacher, and why are they important?

To thrive as a Part-Time Science Teacher, you generally need a strong background in science (such as a degree in biology, chemistry, or physics) and a teaching certification or relevant classroom experience. Familiarity with digital learning platforms, laboratory equipment, and educational technology is often required. Effective communication, classroom management, and adaptability are crucial soft skills for engaging students and delivering lessons efficiently. These skills ensure high-quality instruction, student engagement, and the ability to manage diverse classroom environments within limited teaching hours.

What are some common challenges faced by part-time science instructors, and how can they be managed?

Part-time science instructors often balance multiple commitments, which can make time management a significant challenge. They may find it difficult to coordinate lab sessions, keep up with grading, and provide timely feedback while working limited hours. Building strong communication with full-time faculty, utilizing digital tools for efficient lesson planning, and setting clear boundaries with students can help manage these challenges. Additionally, staying organized and proactive in scheduling can ensure a smooth workflow and maintain a positive teaching experience.

What is the difference between Part Time Science vs Part Time Laboratory Technician?

AspectPart Time SciencePart Time Laboratory Technician
Required CredentialsHigh school diploma or equivalent; some roles may require a degree in scienceHigh school diploma; some positions may require certification or associate degree
Work EnvironmentClassroom, tutoring centers, or remote settingsLaboratories, research facilities, or healthcare settings
Employer & Industry UsageEducational institutions, tutoring companies, online platformsResearch labs, hospitals, biotech firms
Common Search & Comparison IntentUnderstanding part-time science roles for education or tutoringExploring laboratory technician roles for part-time work or entry-level positions

Part Time Science typically involves roles related to education, tutoring, or science communication, often in academic or online settings. In contrast, Part Time Laboratory Technicians work in laboratory environments supporting research or clinical testing. Both roles require some science background but differ mainly in work environment and job responsibilities.

What cities near Draper, UT are hiring for Part Time Science jobs? Cities near Draper, UT with the most Part Time Science job openings:
Part Time Science jobs near you
Infographic showing various Part Time Science job openings in Draper, UT as of June 2026, with employment types broken down into 20% Full Time, 70% Part Time, and 10% Contract. Highlights an 96% Physical, 1% Hybrid, and 3% Remote job distribution, with an average salary of $45,238 per year, or $21.7 per hour.

Data Science - AI Document Understanding, Co-op

Ancestry

Lehi, UT • Remote

Part-time

Re-posted 25 days ago

Job description

About Ancestry:


When you join Ancestry, you join a human-centered company where every person’s story is important. Ancestry®, the global leader in family history, connects everyone with their past so they can discover, preserve, and share their unique family stories. With our unparalleled collection of more than 65 billion records, over 3.5 million subscribers, and over 27 million people in our growing DNA network, customers can discover their family story and gain a new level of understanding about their lives. Over the past 40 years, we’ve built trusted relationships with millions of people who have chosen us as the platform for discovering, preserving, and sharing the most important information about themselves and their families.
We are committed to our location flexible work approach, allowing you to choose to work in the nearest office, from your home, or a hybrid of both (subject to location restrictions and roles that are required to be in the office- see the full list of eligible US locations HERE). We will continue to hire and promote beyond the boundaries of our office locations, to enable broadened possibilities for employee diversity.
Together, we work every day to foster a work environment that's inclusive as well as diverse, and where our people can be themselves. Every idea and perspective is valued so that our products and services reflect the global and diverse clients we serve. 
Ancestry encourages applications from minorities, women, the disabled, protected veterans and all other qualified applicants. Passionate about dedicating your work to enriching people’s lives? Join the curious.

Ancestry is seeking an exceptional and highly motivated AI Engineer / Data Science Co-op to join our AI Applied Science Content team. You’ll play a vital role in the design and implementation of AI Native agentic systems that extract and organize text and image information from billions of historical and genealogical records, enabling customers to discover, share, and connect with their family history. The work will focus on building autonomous, multi-agent workflows capable of complex reasoning, tool use, analysis, and self-correction. You will also work closely with engineering teams to train, optimize, and deploy solutions that promote product development, customer success, and content creation across our Family History business. This is a part-time, work-study-based opportunity designed for active master's and PhD students continuing their education in the fall.

What you will do:

  • Innovate with State-of-the-Art AI: Implement cutting-edge AI solutions for key Document Understanding tasks such as OCR/HTR, transcription, Named Entity Recognition (NER), Relation Extraction (RE), Coreference Resolution, Summarization, and Knowledge Graphs working with diverse genealogical and historical collections spanning newspapers, city directories, family history books, and vital records (i.e., birth, marriage, & death records).

  • Analyze and Optimize Multi-Modal Models: Evaluate the performance of multi-modal models in zero-shot and few-shot learning scenarios for comprehensive document understanding.

  • Architect Agentic Systems: Design and implement multi-agent workflows using frameworks like LangChain, LangGraph, CrewAI, or AutoGen to automate complex multi-step reasoning tasks in historical document analysis.

  • Evaluation & Observability: Establish "LLM-as-a-Judge" frameworks and use tools like Arize Phoenix, DeepEval, or RAGAS to monitor for hallucination, drift, and bias.

  • Collaborate on Cloud Deployment: Partner closely with ML Ops and Data Science Engineers to seamlessly deploy datasets, models, and pipelines in cloud environments.

  • Communicate Insights Effectively: Clearly and confidently present your findings, deliverables, and proposed solutions to technical and non-technical audiences, including teams, stakeholders, and executives.

Who You Are:

  • Currently pursuing an advanced degree (Master's or PhD preferred) in Computer Science, Data Science, Statistics, Mathematics, Linguistics, Engineering or related quantitative field with a strong data focus.

  • Specialization in AI & LLMs including familiarity with foundational models such as GPT, Gemini, Qwen, Llama, Claude, etc.

  • Experience with inference optimization, vLLM, LoRA, QLoRA, quantization, etc.

  • Familiar with embeddings, vector databases, transformer models, with software development experience.

  • Strong proficiency in Python and relevant tools and libraries, including transformer models, multi-modal models, and general NLP (e.g., Hugging Face Transformers, agentic frameworks andworkflows, LangChain, LangGraph, CrewAI, AgentCore).

  • Familiarity with cloud platforms and related AI/ML services such as Google Cloud Platform, GCP, Gemini API, Vertex AI, AWS EC2, S3, SageMaker, Model Registry, and Bedrock is a plus.

Additional Information:

Ancestry is an Equal Opportunity Employer that makes employment decisions without regard to race, color, religious creed, national origin, ancestry, sex, pregnancy, sexual orientation, gender, gender identity, gender expression, age, mental or physical disability, medical condition, military or veteran status, citizenship, marital status, genetic information, or any other characteristic protected by applicable law. In addition, Ancestry will provide reasonable accommodations for qualified individuals with disabilities.

All job offers are contingent on a background check screen that complies with applicable law. For candidates who live in San Francisco, CA, pursuant to the San Francisco Fair Chance Ordinance, Ancestry will consider for employment qualified applicants with arrest and conviction records.

Ancestry is not accepting unsolicited assistance from search firms for this employment opportunity. All resumes submitted by search firms to any employee at Ancestry via-email, the Internet or in any form and/or method without a valid written search agreement in place for this position will be deemed the sole property of Ancestry. No fee will be paid in the event the candidate is hired by Ancestry as a result of the referral or through other means.

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