lead data scientist

Lorenz Engineering, a division of The Salem Group

<div>
 
 Data Scientist (10&ndash;15 Years of Experience)
 
 
 A Data Scientist with 10 to 15 years of experience plays a pivotal role in an organization, harnessing advanced analytics, machine learning, and data-driven insights to guide critical business decisions. This role requires deep expertise in data science, a proven track record of successfully implementing data solutions, and strong leadership capabilities.
 
 
 Key Responsibilities
 
 
 Data Analysis
 
 
 Expertly handle complex data sets, conduct in-depth data analysis, and derive actionable insights by applying advanced statistical and machine learning techniques.
 
 
 Predictive Modeling
 
 
 Develop and deploy sophisticated machine learning models, utilizing algorithms like deep learning, ensemble methods, and neural networks to predict trends, behaviors, and outcomes.
 
 
 Data Visualization
 
 
 Create compelling data visualizations that effectively communicate complex findings and insights using tools like Tableau, Power BI, or custom Python visualizations.
 
 
 Feature Engineering
 
 
 Lead feature engineering efforts to identify and select critical data features, enhancing the predictive power of machine learning models.
 
 
 Statistical Validation
 
 
 Formulate, implement, and test hypotheses, providing robust statistical validation for key business decisions.
 
 
 Algorithm Development
 
 
 Lead the development of machine learning algorithms and their optimization to solve complex business problems.
 
 
 Data Integration
 
 
 Collaborate with IT and data engineering teams to integrate and access data from various sources, data lakes, and data warehouses.
 
 
 Model Deployment
 
 
 Oversee the deployment of machine learning models in production environments to support real-time decision-making and business applications.
 
 
 Experimentation &amp; A/B Testing
 
 
 Design and analyze A/B tests to measure the impact of changes, optimizations, and improvements.
 
 
 Data Ethics
 
 
 Ensure ethical data practices, privacy compliance, and adherence to data protection regulations in all data science initiatives.
 
 
 Cross-functional Collaboration
 
 
 Collaborate closely with cross-functional teams, including engineers, business analysts, domain experts, and executives to understand business requirements and align data science initiatives with organizational goals.
 
 
 Mentorship
 
 
 Provide mentorship and guidance to junior data scientists, fostering their growth and development.
 
 
 Strategic Leadership
 
 
 Act as a strategic leader, influencing data-driven culture across the organization, defining the data science roadmap, and contributing to long-term data strategy.
 
 
 Innovation
 
 
 Stay updated on the latest data science tools, techniques, and trends, continuously innovating and evaluating new technologies to improve data science practices.
 
 
 Qualifications
 
 <ul>
 <li>
 Master&rsquo;s or Ph.D. in a quantitative field preferred (e.g., Computer Science, Statistics, Mathematics, Engineering).
 </li>
 <li>
 10 to 15 years of experience in data science, including an extensive track record of implementing data solutions and driving data-driven decision-making.
 </li>
 <li>
 Proficiency in data analysis tools and programming languages such as Python, R, or Julia.
 </li>
 <li>
 Expert knowledge of machine learning algorithms and their applications.
 </li>
 <li>
 Exceptional skills in data visualization tools like Tableau, Power BI, or data visualization libraries in Python (e.g., Matplotlib, Seaborn).
 </li>
 <li>
 Profound understanding of databases and data manipulation using SQL.
 </li>
 <li>
 Outstanding problem-solving and critical thinking abilities.
 </li>
 <li>
 Strong leadership and communication skills, capable of conveying complex findings and insights to both technical and non-technical stakeholders.
 </li>
 <li>
 Extensive experience with big data technologies and distributed computing frameworks (e.g., Hadoop, Spark).
 </li>
 <li>
 Expertise in data ethics, privacy, and compliance considerations.
 </li>
 </ul>
 
 
 
 
 
 
 
 Lorenz Engineering Benefit Summary
 
 
 
 
 
 EEO
 
 
 
 
 
 The Salem Group provides equal employment opportunity to all qualified employees and applicants for employment without regard to race, color, ancestry, national origin, sexual orientation, marital status, religion, age, disability, gender identity, results of genetic testing, service in the military, or any other category protected by law.
 
 
 
 
 
 Salem utilizes technology-assisted tools, including artificial intelligence, to support recruiting, applicant matching, and related employment processes. Final employment decisions are made by Salem personnel
 
 
 
 
 
 
 
 
 
 
 AI Notice:
 
 
 
 
 
 Salem utilizes technology-assisted tools, including artificial intelligence, to support recruiting, applicant matching, and related employment processes. Final employment decisions are made by Salem personnel.
 
</div>

Data Scientist

Uber

<div>
 
 Employer:
 
 Uber Technologies, Inc.
 
 
 
 Job Title:
 
 Sr Data Scientist, Tech
 
 
 
 Job Location:
 
 New York, New York
 
 
 
 Job Type:
 
 Full Time
 
 
 
 Rate of Pay:
 
 $261,248 to $313,498 per year
 
 
 You will be eligible to participate in Uber's bonus program, and may be offered other types of comp. You will also be eligible for various benefits. More details can be found at the following link https://www.uber.com/careers/benefits .
 
 
 
 Duties:
 
 Build prototype software solutions to automate business processes to drive operational efficiency. Leverage data to understand business problems and opportunities for automation, enabling teams to action levers that drive incremental business value without increasing manual burden. Conduct architecture and code reviews with Engineering teams to enable prototype solutions through internal and external APIs, finding opportunities to apply new AI technologies and tools. Monitor and track performance of automated activities to ensure business continuity and re-assess relevance periodically, and move beyond the prototype stage where relevant in partnership with Engineering and Product teams. Manage an in-person team that carries out similar duties as above, and oversee a remote team of analysts that create dashboards and reports to communicate results and monitor key metrics, through analysis and building data pipelines. Develop end-to-end solutions to abstract business and engineering problems related to funnel optimization, user engagement, and user experience. Supervise at least 1 Data Scientist / 15-2051; Data Scientists. May telecommute.
 
 
 Employer will accept a Bachelor's degree in Business, Economics, Engineering (Any), Data Science, Analytics, Computer Science, or related field, followed by five years of progressive, post-baccalaureate experience in the job offered or in a related occupation.
 
 
 
 Position Requires
 
 
 
 <ul>
 <li>
 R or Python;
 </li>
 <li>
 SQL;
 </li>
 <li>
 Designing and overseeing data products, analytics, and automation solutions;
 </li>
 <li>
 Leading technical teams in automation, analytics, or data science;
 </li>
 <li>
 Developing end-to-end prototype solutions to automate business processes and improve efficiency;
 </li>
 <li>
 Identifying opportunities for business and operation optimization and efficiency;
 </li>
 <li>
 Machine learning and AI capabilities and identifying use cases to drive automation;
 </li>
 <li>
 Deploying code and developing best practices for automation capabilities.
 </li>
 </ul>
</div>

Sr Data Scientist, Tech

JPMorganChase

<div>JOB DESCRIPTION<div><div> 
Join Consumer Bank Marketing Analytics to transform data into insight and improve how customers discover, open, and use our products. As a Data Scientist Lead, you will lead cross-line of business analytics efforts that streamline referrals and modernize marketing offer discovery. You will partner across Product, Technology, Marketing, Customer Experience, and Risk/Compliance to shape strategy and drive business results. You will use advanced analytics and AI-enabled tooling to accelerate delivery, improve consistency, and raise the bar on measurement and decisioning.
Job summary
As a Data Scientist Lead in Consumer Bank Marketing Analytics, you will own the analytics strategy for marketing offer transformation initiatives that improve offer discovery, fulfillment, and referral experiences for customers and bankers. In a cross-functional quad, you will define success metrics and guardrails, size and evaluate experiments, and deliver dashboards and reporting that enable consistent, reliable decision-making. You will translate complex analyses into clear, decision-ready recommendations for senior stakeholders and align partners on the highest-impact work. You will maintain a rigorous controls environment and strong data quality practices while collaborating closely with Risk/Compliance. You will mentor junior data scientists and help build shared measurement standards across journeys and channels.
Job responsibilities
<ul><li>Lead the analytics strategy, planning, and execution for marketing offer transformation by turning business problems into hypotheses, measurement plans, and decision-ready insights.</li><li>
Shape the offer transformation roadmap by identifying capability gaps (data, platform, process, and experience), quantifying customer impact and business value, and aligning the quad on highest-impact workstreams.</li><li>
Provide actionable analytics for referral capability enhancements and offer journey optimization, measuring impact on acquisition, activation, engagement, fulfillment, and quality outcomes.</li><li>
Lead experimentation and test design by sourcing data, defining success and guardrail metrics, sizing A/B tests, analyzing results, and communicating recommendations to the quad and senior leadership.</li><li>
Define and govern a cross-line of business measurement framework by establishing KPIs, standardizing metric definitions, and aligning success metrics and guardrails across channels and journeys.</li><li>
Build and continuously improve dashboards and reporting to enable reliable decision-making, improving usability, timeliness, data quality controls, and self-service consumption.</li><li>
Drive advanced analytics to identify journey friction, improve offer fulfillment, and increase customer engagement across digital and banker-assisted experiences.</li><li>
Apply AI tools and automation to streamline analysis workflows, reduce cycle time, and accelerate insight delivery with consistent quality.</li><li>
Provide leadership and mentorship to junior data scientists as a subject matter expert for offer fulfillment experiences and measurement practices.</li><li>
Maintain a rigorous controls environment to ensure accurate, timely, and well-governed analyses, including documentation, data validation, and appropriate Risk/Compliance partnership.</li></ul>
Required qualifications, capabilities, and skills
<ul><li>Bachelor&rsquo;s degree in Data Science, Statistics, Mathematics, Computer Science, Business Analytics, MIS, or a related field.</li><li>
5+ years of experience in analytics/data science supporting customer journeys, digital products, or operational workflows.</li><li>
5+ years of hands-on experience with SQL and Python.</li><li>
5+ years of experience with Adobe Analytics, Tableau, and Alteryx (or comparable tools).</li><li>
Proven experience defining KPIs and building measurement frameworks, including guardrails and data quality checks.</li><li>
Demonstrated experience sizing and evaluating A/B experiments and communicating results to business and technical audiences.</li><li>
Strong dashboarding/BI skills, including metric governance, performance optimization, and executive-ready reporting.</li><li>
Strong slide-writing and storytelling skills to deliver clear narratives and recommendations.</li><li>
Excellent communication, influence, and stakeholder management skills, with ability to lead through ambiguity and drive outcomes.</li><li>
Strong communication skills to translate complex analyses into clear narratives for executive, business, and technical audiences.</li><li>
Proven ability to take initiative, influence others, and achieve results.</li></ul>
Preferred qualifications, capabilities, and skills
<ul><li>Experience in financial services and/or other regulated environments.</li><li>
Demonstrated experience using AI coding tools (for example, GitHub Copilot, Claude Code, Cortex) to improve productivity and accelerate insights.</li><li>
Intellectually curious and eager to become a subject matter expert in your focus area.</li><li>
Creative problem solver with strong analytical rigor.</li><li>
Strong communicator who can build relationships with key stakeholders.</li></ul></div></div><div>
Generated with LLM Suite General</div>
ABOUT US 
Chase is a leading financial services firm, helping nearly half of America&rsquo;s households and small businesses achieve their financial goals through a broad range of financial products. Our mission is to create engaged, lifelong relationships and put our customers at the heart of everything we do. We also help small businesses, nonprofits and cities grow, delivering solutions to solve all their financial needs.
We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process.
We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants&rsquo; and employees&rsquo; religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.
Equal Opportunity Employer/Disability/Veterans 
 
 
ABOUT THE TEAM 
<div>
Our Consumer &amp; Community Banking division serves our Chase customers through a range of financial services, including personal banking, credit cards, mortgages, auto financing, investment advice, small business loans and payment processing. We&rsquo;re proud to lead the U.S. in credit card sales and deposit growth and have the most-used digital solutions &ndash; all while ranking first in customer satisfaction.</div><div> 
 
</div><div>The CCB Data &amp; Analytics team responsibly leverages data across Chase to build competitive advantages for the businesses while providing value and protection for customers. The team encompasses a variety of disciplines from data governance and strategy to reporting, data science and machine learning. We have a strong partnership with Technology, which provides cutting edge data and analytics infrastructure. The team powers Chase with insights to create the best customer and business outcomes.</div></div>

Data Scientist Lead - Consumer Bank Marketing Analytics - VP

Data Scientist, Analytics (Technical Leadership)

Amazon.com

<div><h2 class="jobSectionHeader">DESCRIPTION</h2>
The Artificial General Intelligence (AGI) team is seeking a dedicated, skilled, and innovative Applied Scientist with a robust background in machine learning, statistics, quality assurance, auditing methodologies, and automated evaluation systems to ensure the highest standards of data quality, to build industry-leading technology with Large Language Models (LLMs) and multimodal systems. 
 
Key job responsibilities 
As part of the AGI team, an Applied Scientist will collaborate closely with core scientist team developing Amazon Nova models. They will lead the development of comprehensive quality strategies and auditing frameworks that safeguard the integrity of data collection workflows. This includes designing auditing strategies with detailed SOPs, quality metrics, and sampling methodologies that help Nova improve performances on benchmarks. The Applied Scientist will perform expert-level manual audits, conduct meta-audits to evaluate auditor performance, and provide targeted coaching to uplift overall quality capabilities. A critical aspect of this role involves developing and maintaining LLM-as-a-Judge systems, including designing judge architectures, creating evaluation rubrics, and building machine learning models for automated quality assessment. The Applied Scientist will also set up the configuration of data collection workflows and communicate quality feedback to stakeholders. An Applied Scientist will also have a direct impact on enhancing customer experiences through high-quality training and evaluation data that powers state-of-the-art LLM products and services. 
 
A day in the life 
An Applied Scientist with the AGI team will support quality solution design, conduct root cause analysis on data quality issues, research new auditing methodologies, and find innovative ways of optimizing data quality while setting examples for the team on quality assurance best practices and standards. Besides theoretical analysis and quality framework development, an Applied Scientist will also work closely with talented engineers, domain experts, and vendor teams to put quality strategies and automated judging systems into practice.<h2 class="jobSectionHeader">
BASIC QUALIFICATIONS</h2><ul><li>Master's degree in computer science, mathematics, statistics, machine learning or equivalent quantitative field</li><li>Experience programming in Java, C++, Python or related language</li><li>Experience with SQL and an RDBMS (e.g., Oracle) or Data Warehouse</li></ul><h2 class="jobSectionHeader">
PREFERRED QUALIFICATIONS</h2><ul><li>Experience implementing algorithms using both toolkits and self-developed code</li><li>Have publications at top-tier peer-reviewed conferences or journals</li></ul> 
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. 
 
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you&rsquo;re applying in isn&rsquo;t listed, please contact your Recruiting Partner. 
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life &amp; AD&amp;D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits. 
USA, MA, Boston - 136,000.00 - 184,000.00 USD annually 
USA, WA, BELLEVUE - 136,000.00 - 184,000.00 USD annually</div>

Applied Scientist, Artificial General Intelligence, AGI Data Services

Intuit

<div><h2 class="jobSectionHeader">Overview</h2>
Intuit enables millions of small and mid-sized businesses to grow through marketing automation and customer intelligence. As we accelerate toward becoming an AI-driven platform, Product Data Science must evolve to operate at a new level of technical sophistication, scale, and strategic influence. 
We are seeking a Principal Data Science Leader to partner with the leadership team and lead the AI transformation of the Product Data Science organization. This leader will modernize how data science is practiced by advancing modeling capabilities, experimentation rigor, generative AI adoption, and scalable decision systems while driving measurable revenue, growth, and expert network outcomes. 
This role requires a proven track record of building durable data science capabilities and production-grade solutions, not just delivering analyses. The ideal candidate will elevate the craft across the organization, establish higher technical standards, and position data science as a strategic force multiplier for product, growth, and expert performance. 
Responsibilities
Strategic Leadership<ul><li>
Define and lead the multi-year vision for Product Data Science, aligning AI, modeling, and experimentation investments with product strategy and measurable business outcomes.</li><li>
Partner with Data Science leadership to transform the function into an AI-native organization by modernizing tools, workflows, technical standards, and scalable decision systems.</li><li>
Outcome-Driven Product Impact</li><li>
Own revenue and growth accountability for data science-driven initiatives, ensuring modeling, experimentation, and AI investments are directly tied to measurable business outcomes and prioritized for maximum impact.</li><li>
Lead the rapid development and deployment of predictive models, causal inference frameworks, and LLM-enabled solutions, leveraging modern AI tools to accelerate learning velocity and reduce time from insight to decision.</li><li>
Drive a high-speed experimentation culture, balancing rigor with agility, so teams continuously test, learn, and iterate. Translate insights into scalable impact with clear post-launch accountability.</li></ul> 
Expert Optimization<ul><li>
Build and own the data science framework for expert optimization: connecting expert skill signals, product and tool usage patterns, and downstream performance outcomes into a unified model of expert quality and capacity.</li><li>
Develop skill-to-outcome models that link expert proficiency across product domains (tool adoption, workflow adherence, knowledge depth) to measurable service quality metrics, enabling targeted coaching, routing, and capacity decisions.</li><li>
Partner with Expert Network and Operations leadership to translate expert behavioral signals (product usage patterns, interaction telemetry, knowledge assessments) into actionable intelligence. Identify which skills drive quality outcomes, which tool gaps create friction, and how to close both at scale.</li><li>
Design and scale experimentation frameworks to rigorously measure the causal impact of training interventions, tooling changes, and product investments on expert performance outcomes such as resolution quality, customer satisfaction, and proficiency scores.</li><li>
Build expert lifecycle analytics from onboarding through proficiency attainment, identifying acceleration levers and friction points that predict long-term performance and retention.</li><li>
Partner with product teams to close the loop between product and tool design and expert outcomes, surfacing where underutilization or misuse of tooling is suppressing quality and feeding those signals back into roadmap decisions.</li></ul> 
Capability Building and Craft Elevation<ul><li>
Champion and scale durable Product Data Science capabilities by establishing rigorous standards across modeling, experimentation, model governance, and AI-enabled workflows. Raise the technical bar through structured reviews, reusable frameworks, and clear quality benchmarks.</li><li>
Accelerate adoption of modern AI tools, LLMs, and automation to increase productivity, technical depth, and organizational leverage across the Data Science team.</li><li>
Mentor, develop, and retain top data science talent by fostering a culture of ownership, technical excellence, and continuous learning.</li></ul> 
Qualifications<ul><li>
10+ years of experience in Product Data Science with a demonstrated track record of personally building, shipping, and scaling high-impact models and experimentation frameworks that drove measurable revenue and growth outcomes.</li><li>
Proven experience transforming data science practices, establishing modeling standards, experimentation rigor, reusable frameworks, and AI-native workflows across teams.</li><li>
Deep technical expertise in SQL and Python, with strong command of statistical modeling, causal inference, experimentation design, and machine learning at production scale.</li><li>
Hands-on experience applying LLMs and modern AI tooling to accelerate insight generation, modeling workflows, and decision velocity.</li><li>
Demonstrated ability to influence senior cross-functional leaders and drive strategic outcomes without direct authority.</li><li>
Strong mentorship track record, with evidence of elevating senior data scientists and raising the technical bar of an organization.</li><li>
Master's degree or higher in Statistics, Computer Science, Economics, Applied Mathematics, Machine Learning, or a related quantitative field.</li><li>
Deep understanding of growth science, customer lifecycle value, segmentation, and personalization at scale.</li><li>
Experience productionizing AI-driven decision systems in complex product ecosystems.</li><li>
Familiarity with multi-product ecosystems and cross-sell and attach strategies within platform businesses.</li><li>
Experience building behavioral analytics or skill and performance optimization systems in marketplace, gig, or expert network contexts, connecting workforce supply-side signals to customer demand-side outcomes.</li><li>
Prior work with human-in-the-loop AI systems where expert or agent quality is a lever for product performance.</li></ul> 
Intuit provides a competitive compensation package with a strong pay for performance rewards approach. This position may be eligible for a cash bonus, equity rewards and benefits, in accordance with our applicable plans and programs (see more about our compensation and benefits at Intuit&reg;: Careers | Benefits). Pay offered is based on factors such as job-related knowledge, skills, experience, and work location. To drive ongoing fair pay for employees, Intuit conducts regular comparisons across categories of ethnicity and gender. The expected base pay range for this position is:<div>
Bay Area California $ 247,500- 335,000</div><div>
Southern California $ 241,000- 326,500</div></div>

Principal Data Scientist - Expert Optimization, ICS Data Science

BayCare Health System

<div><div><h3 class="jobSectionHeader">Join BayCare as a Clinical Laboratory Scientist Coordinator
</h3>Location: FSED - South Lakeland
 
Facility: BayCare Health System, FSED Lab
 
Shift: Days | Sunday &ndash; Tuesday, 6:00 AM &ndash; 6:00 PM
 
Schedule: Full-Time | Onsite
 
Weekend Work: Every Weekend
<h3 class="jobSectionHeader">About BayCare
</h3>At BayCare, we are proud to be one of the largest employers in the Tampa Bay area. Our network consists of 16 community‑based hospitals, a long-term acute care facility, home health services, outpatient centers and thousands of physicians. With the support of more than 30,000 team members, we promote a forward‑thinking philosophy that&rsquo;s built on a foundation of trust, dignity, respect, responsibility and clinical excellence.
<h3 class="jobSectionHeader">Role Overview
</h3>As a Clinical Laboratory Scientist Coordinator , you will lead daily laboratory operations while ensuring high-quality diagnostic services, regulatory compliance, and team development.
Key responsibilities include:
<ul><li>Coordinating and leading daily laboratory operations, including scheduling and supervisory responsibilities
</li><li>Prioritizing, delegating, and overseeing all phases of the laboratory process
</li><li>Ensuring adherence to all laboratory policies, procedures, and quality standards
</li><li>Overseeing quality assurance and quality management programs and addressing deviations as needed
</li><li>Ensuring compliance with regulatory agencies and system-wide requirements, including proficiency testing
</li><li>Leading staff education, training, and competency validation
</li><li>Serving as a mentor, trainer, and resource for laboratory team members
</li><li>Assisting with data collection and monitoring to support laboratory performance goals
</li><li>Supporting operational leadership responsibilities in the absence of a manager or supervisor
</li></ul><h3 class="jobSectionHeader">Qualifications
</h3><h4 class="jobSectionHeader">Education
</h4>Required:
<ul><li>Bachelor&rsquo;s degree in Biological Science OR a related Clinical Science field
</li></ul><h4 class="jobSectionHeader">Experience
</h4>Required:
<ul><li>4 Years of Clinical laboratory experience
</li></ul><h4 class="jobSectionHeader">Licensure / Certification
</h4>Required:
<ul><li>State of Florida Clinical Laboratory Technologist License
</li></ul><h3 class="jobSectionHeader">What We Offer
</h3>BayCare provides a competitive total rewards package designed to support your career and well‑being, including:
<ul><li>Comprehensive Medical, Dental &amp; Vision Benefits
</li><li>Paid Time Off
</li><li>Tuition Assistance
</li><li>401(k) Match plus Annual Employer Contribution
</li><li>Wellness programs and community perks
</li></ul><h3 class="jobSectionHeader">Take the Next Step
</h3>Step into a leadership role at BayCare and help ensure high-quality laboratory operations that support exceptional patient care.
Apply today to join BayCare as a Clinical Laboratory Scientist Coordinator!
BayCare is an Equal Opportunity Employer. Veterans and individuals with disabilities are encouraged to apply.</div></div>

Clinical Laboratory Scientist Coordinator

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