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$12

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$48

How much do scientific associate jobs pay per hour?

As of Sep 7, 2026, the average hourly pay for scientific associate in Texas is $29.33, according to ZipRecruiter salary data. Most workers in this role earn between $17.93 and $37.40 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a scientific associate?

Thriving as a Scientific Associate requires a strong background in biological or chemical sciences, typically supported by a relevant bachelor's or master's degree and laboratory experience. Familiarity with laboratory information management systems (LIMS), data analysis software, and standard lab equipment is essential. Attention to detail, problem-solving abilities, and effective teamwork are crucial soft skills for this role. These competencies ensure accurate research results, efficient collaboration, and compliance with scientific and safety standards.

How does a scientific associate typically collaborate with senior scientists and other team members on ongoing research projects?

Scientific Associates play a key role in supporting research initiatives by working closely with senior scientists and cross-functional teams. They often assist with experimental design, data collection, and analysis, while also helping to troubleshoot technical issues in the lab. Regular communication and collaboration are essential, as Scientific Associates frequently participate in team meetings, present findings, and contribute to problem-solving discussions. This collaborative environment not only enhances project outcomes but also provides valuable opportunities for learning and professional development.

What is the difference between Scientific Associate vs Laboratory Technician?

AspectScientific AssociateLaboratory Technician
Required CredentialsBachelor's degree in science or related field; some roles may require a master'sAssociate's degree or relevant certification; some roles may require a bachelor's
Work EnvironmentResearch labs, pharmaceutical companies, academic institutionsClinical labs, research facilities, industrial laboratories
Employer & Industry UsageResearch and development, biotech, pharmaceuticals, academiaHealthcare, diagnostics, manufacturing, research

Both roles involve laboratory work, but Scientific Associates typically engage in more complex research tasks and data analysis, while Laboratory Technicians focus on routine testing and sample preparation. The choice depends on your education level and career goals within scientific and laboratory settings.

What does a scientific associate do?

A scientific associate conducts experiments, collects and analyzes data, and supports research projects in laboratories or field settings. They often use specialized tools and follow safety protocols, and may require knowledge of scientific methods and technical skills. Their work helps advance scientific understanding and supports research objectives.

What are the most commonly searched types of Scientific jobs in Texas?

The most popular types of Scientific jobs in Texas are:

What cities in Texas are hiring for Scientific Associate jobs?

Cities in Texas with the most Scientific Associate job openings:

Scientific Associate jobs near you
Infographic showing various Scientific Associate job openings in Texas as of August 2026, with employment types broken down into 1% As Needed, 70% Full Time, 25% Part Time, 1% Temporary, 2% Contract, and 1% Nights. Highlights an 96% Physical, 1% Hybrid, and 3% Remote job distribution, with an average salary of $60,998 per year, or $29.3 per hour.

Internal Audit, Asset Wealth Management - Senior Associate - Data Scientist

JPMorgan Chase & Co.

Plano, TX • On-site

$95 - $135/hr

Other

Posted 26 days ago

JPMorgan Chase & Co. rating

7.9

Company rating: 7.9 out of 10

Based on 500 frontline employees who took The Breakroom Quiz

77th of 175 rated banks

Job description

Join our dynamic Audit Analytics team, where you'll leverage advanced data science and analytics to shape the future of audit. You'll collaborate with talented colleagues and stakeholders, using innovative tools and techniques to deliver impactful solutions that enhance risk management and business value.

As an Audit Analytics & Data Science Associate within our Asset & Wealth Management Audit Team, you will deliver comprehensive analytics and data science solutions across the audit lifecycle. You'll partner with audit leads and stakeholders to translate objectives into actionable insights, engineer scalable solutions, and communicate findings that drive informed decision-making. Your work will help strengthen risk management and support continuous improvement in audit processes.

Job Responsibilities
  • Deliver end-to-end analytics and data science solutions across the audit lifecycle, from problem framing and requirements through data acquisition, analysis/modeling, visualization, and deployment using tools such as SQL, Python, Alteryx, Databricks, Tableau, Agentic Studio, Smart SDK, and related platforms
  • Translate audit objectives into clear analytic hypotheses and test designs, selecting appropriate methods to support risk-based audit scoping and execution
  • Partner closely with audit leads and stakeholders to shape and refine analytics and data science requirements, proactively managing relationships, expectations, and communications
  • Engineer repeatable, scalable analytics and data science solutions—including datasets, reusable code modules, workflows, dashboards, and templates—to improve efficiency and enable auditor self-service
  • Design and develop solutions for non-audit cycle activities, including continuous auditing, continuous monitoring, automated testing, advanced testing, and event/trigger-based analytics
  • Apply strong data management and governance practices to ensure analytics are reliable, auditable, and reproducible
  • Implement quality controls for analytic outputs, including validation checks, reasonableness testing, peer review, and clear documentation
  • Manage multiple concurrent deliverables by planning work, prioritizing effectively, and meeting timelines and budget expectations
  • Continuously evaluate and adopt new tools and techniques to improve team effectiveness and recommend process enhancements
  • Communicate insights clearly to varied audiences, tailoring messaging and visuals to drive understanding and action
  • Contribute to team knowledge-sharing by providing perspectives on analytics and data science value, and supporting enablement through guidance, demos, and training
Required Qualifications, Capabilities, and Skills
  • Bachelor’s degree in Computer Science, Data Analytics, Data Science, Information Systems, Engineering, or a related discipline (or equivalent practical experience)
  • Minimum 3 years of experience in Audit, Data Analytics, Data Science, Risk/Controls, or a closely related role
  • Demonstrated experience working with large, complex datasets, performing data wrangling, validation, enrichment, and building analytics and data science solutions
  • Proven track record of building and delivering repeatable, production-ready data science and analytical solutions such as automated workflows, dashboards, anomaly detection, or model development
  • Strong understanding of data ecosystems, including databases, data warehouses/lakes, ETL/ELT patterns, and APIs/files, and how technology design influences risk, controls, and auditability
  • Working knowledge of technology and data risks/controls and the ability to apply this experience when designing solutions
  • Excellent written and verbal communication skills, with the ability to explain technical concepts to non-technical audiences and build partnerships
  • Strong critical thinking and structured problem-solving skills, able to frame ambiguous questions, test hypotheses, and identify practical solutions under time constraints
  • Ability to manage and deliver multiple concurrent tasks with attention to detail, effective prioritization, and follow-through against timelines
  • Working knowledge of data management principles such as data quality, lineage, metadata, governance, privacy/access considerations, and documentation practices that support reproducibility
  • Self-motivated and proactive, demonstrating accountability, sound judgment, and the ability to operate through ambiguity while maintaining high standards
Preferred Qualifications, Capabilities, and Skills
  • Experience with workflow enablement and agentic tooling, such as Agentic Studio, Smart SDK, or AI code assistance tools (Claude Code, GitHub Copilot)
  • Experience with cloud data platforms such as Databricks or Snowflake
  • Experience with visualization analytics tools such as Tableau or similar platforms
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