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Data Science Assistant Jobs in Arizona (NOW HIRING)

Design, develop, and implement Generative AI solutions including chatbots and AI assistants. * Work ... Proficiency in Python and common data science libraries/frameworks. * Experience with cloud ...

Design, develop, and implement Generative AI solutions including chatbots and AI assistants. Work ... Proficiency in Python and common data science libraries/frameworks. Experience with cloud platforms ...

Data Scientist

Tempe, AZ · Hybrid

$60K - $100K/yr

Participate in collection, conversion, and assembly of data in a variety of formats. * Assist in ... About you * BS or BA in data science, computer science, mathematics, statistics, or other related ...

These efforts will encompass exploring AI solutions that serve as intelligent work assistants ... Bachelor's degree in mathematics, computer science, statistics, economics, finance, actuarial ...

These efforts will encompass exploring AI solutions that serve as intelligent work assistants ... Bachelor's degree in mathematics, computer science, statistics, economics, finance, actuarial ...

Lead AI and Data Science Engineer - Manager

Tempe, AZ · On-site

$98K - $129K/yr

Lead AI and Data Science Engineer - Manager Position Summary Our Human Capital practice is at the ... Build tools and capabilities that assist with data ingestion, feature engineering, data management ...

Data Scientist - A365

Fort Huachuca, AZ · On-site +1

$85K - $95K/yr

Education and Background Bachelor's in computer science, Cybersecurity, Data Science, Information ... These tools assist our recruitment team but do not replace human judgment. Final hiring decisions ...

$85K - $95K/yr

Education and Background Bachelor's in computer science, Cybersecurity, Data Science, Information ... These tools assist our recruitment team but do not replace human judgment. Final hiring decisions ...

These efforts will encompass exploring AI solutions that serve as intelligent work assistants ... Bachelor's degree in mathematics, computer science, statistics, economics, finance, actuarial ...

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Data Science Assistant information

What are Data Science Assistants?

Data Science Assistants are professionals who support data scientists and analytics teams by handling tasks such as data collection, data cleaning, preparing datasets, conducting preliminary analyses, and creating visualizations. They often work with large datasets, assist in maintaining data integrity, and help automate routine processes. Their role allows data scientists to focus on more complex modeling and analytical work, making the overall workflow more efficient. Data Science Assistants typically have a foundational understanding of statistics, programming (such as Python or R), and data management tools.

What are the key skills and qualifications needed to thrive as a Data Science Assistant, and why are they important?

To thrive as a Data Science Assistant, you need a solid understanding of statistics, data analysis, and programming (often with a background in mathematics, computer science, or a related field). Familiarity with tools like Python or R, data visualization software, and experience with databases or spreadsheet systems are typically required. Attention to detail, strong problem-solving abilities, and effective communication set outstanding candidates apart. These skills are crucial for supporting data-driven decision-making and ensuring accurate, actionable insights for organizations.

Is 40 too late for data science?

Data science assistants can enter the field at any age, as success depends on skills, experience, and continuous learning. Many professionals transition into data science later in their careers by acquiring relevant knowledge in programming, statistics, and tools like Python or R. Age is not a barrier if you develop the necessary competencies and stay current with industry trends.

How does a Data Science Assistant typically collaborate with data scientists and other team members on projects?

As a Data Science Assistant, you will frequently support data scientists by preparing datasets, conducting preliminary data analysis, and creating visualizations. You will often work closely with analysts, engineers, and subject matter experts to gather requirements and ensure data is cleaned and formatted appropriately. Collaboration is a key part of the role, as you may participate in team meetings, share findings, and help with documentation to keep projects running smoothly. This supportive environment provides an excellent opportunity to learn from experienced professionals and gain exposure to the full data science workflow.

What is the difference between Data Science Assistant vs Data Analyst?

AspectData Science AssistantData Analyst
Required CredentialsBachelor's in Data Science, Statistics, or related fieldBachelor's in Statistics, Mathematics, or related field
Work EnvironmentTech companies, research labs, data-driven departmentsBusiness, finance, marketing, healthcare sectors
Employer & Industry UsageUsed in data science teams for supporting models and analysisUsed across industries for interpreting data and generating reports

While both roles involve working with data, a Data Science Assistant typically supports data science projects, focusing on data preparation and model testing. A Data Analyst primarily interprets data to generate insights and reports. The roles overlap in skills and work environments but differ in their core responsibilities and focus areas.

What is a data scientist assistant?

A data scientist assistant supports data scientists by collecting, cleaning, and analyzing data, often using tools like Python or R. They help prepare reports, build models, and may need knowledge of statistics and data visualization to contribute effectively to data projects.

Is AI replacing data scientists?

AI is transforming the role of data scientists by automating routine tasks such as data cleaning and basic analysis, but it does not replace the need for skilled professionals to interpret results, develop models, and make strategic decisions. Data scientists are increasingly required to work alongside AI tools, focusing on complex problem-solving, model development, and domain expertise. Continuous learning and proficiency in programming languages like Python and tools such as machine learning frameworks remain essential for the role.

Which is better, DS or CS?

For a Data Science Assistant role, both Data Science (DS) and Computer Science (CS) provide valuable skills; DS focuses on data analysis, modeling, and visualization, while CS emphasizes algorithms, programming, and software development. The choice depends on the specific job requirements and your career goals, but familiarity with programming languages like Python or R and understanding of data tools are essential in both fields.
What are the most commonly searched types of Data Science jobs in Arizona? The most popular types of Data Science jobs in Arizona are:
What are popular job titles related to Data Science Assistant jobs in Arizona? For Data Science Assistant jobs in Arizona, the most frequently searched job titles are:
Infographic showing various Data Science Assistant job openings in Arizona as of June 2026, with employment types broken down into 1% As Needed, 85% Full Time, 12% Part Time, 1% Temporary, and 1% Contract. Highlights an 98% Physical, 1% Hybrid, and 1% Remote job distribution.

Data Scientist, Data & Science Solutions

Caris Life Sciences

Tempe, AZ

Full-time

Posted 5 days ago


Job description

At Caris, we understand that cancer is an ugly word-a word no one wants to hear, but one that connects us all. That's why we're not just transforming cancer care-we're changing lives.

We introduced precision medicine to the world and built an industry around the idea that every patient deserves answers as unique as their DNA. Backed by cutting-edge molecular science and AI, we ask ourselves every day:"What would I do if this patient were my mom?"That question drives everything we do.

But our mission doesn't stop with cancer. We're pushing the frontiers of medicine and leading a revolution in healthcare-driven by innovation, compassion, and purpose.

Join us in our mission to improve the human condition across multiple diseases. If you're passionate about meaningful work and want to be part of something bigger than yourself, Caris is where your impact begins.

Position Summary

Caris Life Sciences is seeking a data scientist to expand, test, and validate a suite of molecular biomarkers aimed to improve the standard of care for patients undergoing treatment for cancer. This is a research role within the Caris signature development program and responsibilities will center on statistical or machine-learning derived predictions of phenotypic treatment response built from the genotypic data types available on Caris molecular sequencing platforms. A successful candidate will have the analytical, code-oriented mindset to create reproducible data science pipelines, and the communication skills to discuss the implications of the scientific results with our medical professionals.

Job Responsibilities

  • Contribute to analytics and research that support internal stakeholders and external partners.

  • Assist in the development and evaluation of molecular signatures and analytical approaches that leverage Caris' data to support partner research and drug discovery strategies.

  • Support preparation of analytical results and figures for internal reviews and client-facing discussions.

  • Develop and maintain tools, workflows, and automated solutions to scale data analytics and data science operations.

  • Support the Biopharma Solutions team with feasibility assessments and tooling to optimize workflows.

  • Write well-structured, well-documented, and reproducible code, including efficient queries and organized codebases.

    Required Qualifications

    • PhD in Computational Biology, Bioinformatics, Mathematics, Data Science, Engineering, or related scientific field.

    • Strong programming skills in Python or R, with experience developing reproducible analysis workflows.

    • Experience with Linux ecosystem, Git, and queries from SQL or related database families.

    • Experience with molecular genetics data and/or multimodal real-world data (RWD).

    • Ability to translate biological and scientific questions into analytical or statistical approaches and deliver data-driven insights.

    • Strong verbal and written communication skills, with the ability to explain complex technical concepts in clear language.

    Preferred Qualifications

    • Experience with interpretation of clinical health records including Electronic Health Records, insurance claims data, or patient histories.

    • Experience collaborating directly with external partners or clients, particularly in biopharma or healthcare.

    • Good code documentation practices and experience with workflow management packages.

    • Experience working in cloud or HPC clusters.

    Physical Demands

    • Will work at a computer most of the time, with some time spent collaborating with subject matter experts and business group leaders either in person or through remote conferencing.

    • Visual acuity and analytical skill to distinguish fine detail.

    • Must possess ability to sit and/or stand for long periods of time.

    Training

    • All job specific, safety, and compliance training are assigned based on the job functions associated with this employee.

    Other

    • This position may require periodic travel and some evenings, weekends, and/or holidays.

    Conditions of Employment: Individual must successfully complete pre-employment process, which includes criminal background check, drug screening, credit check( applicable for certain positions) and reference verification.

    This job description reflects management's assignment of essential functions. Nothing in this job description restricts management's right to assign or reassign duties and responsibilities to this job at any time.

    Caris Life Sciences is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, religion, color, national origin, gender, gender identity, sexual orientation, age, status as a protected veteran, among other things, or status as a qualified individual with disability.