Data scientist jobs in Gainesville, FL

We are looking for a Data Scientist with expertise in optimization and forecasting to help improve how we manage labor, staffing, and operational resources across our retail locations. This role is critical in building models and decision-support tools that ensure the right people, in the right place, at the right time - balancing customer service, efficiency, and cost. You will work closely with Operations, Finance, and Store Leadership teams to deliver practical solutions that improve labor planning, scheduling, and demand forecasting. The right candidate will be confident, resourceful, and excited to own both the technical and business-facing aspects of applying data science in a fast-paced retail environment. Responsibilities Build and maintain forecasting models (time-series, machine learning, and statistical) for sales and transactions. Develop and deploy optimization models (linear/mixed-integer programming, heuristics, simulation) to improve workforce scheduling and labor allocation. Partner with operations and finance to translate forecasts into actionable staffing and labor plans that reduce costs while maintaining service levels. Build dashboards and automated tools to track forecast accuracy, labor KPIs, and staffing effectiveness. Provide insights and “what-if” scenario modeling to support strategic workforce and budget planning. Knowledge, Skills, And Abilities Strong foundation in forecasting techniques (time-series models, regression, machine learning) and optimization methods (linear/mixed-integer programming, heuristics, simulation). Proficiency in Python or R for modeling and analysis, along with strong SQL skills for working with large-scale datasets. Knowledge of statistics, probability, and applied mathematics to support predictive and prescriptive modeling. Experience building and deploying predictive models, optimization tools, and decision-support solutions that drive measurable business outcomes. Strong data storytelling and visualization skills using tools such as Power BI, Tableau, or Looker. Ability to translate analytical outputs into clear, actionable recommendations for non-technical stakeholders. Strong collaboration skills with the ability to partner cross-functionally with Operations, Finance, and Store Leadership to drive adoption of data-driven approaches. Ability to work independently and resourcefully, combining technical depth with practical problem-solving to deliver results in a fast-paced environment. Education And Requirements Required: Bachelor's or Master's degree in Data Science, Statistics, Applied Mathematics, Industrial Engineering, Operations Research, or related field. Minimum 2-3 years of professional experience in Data Science or a related area. Strong skills in time-series forecasting (e.g., ARIMA, Prophet, ML-based approaches). Proficiency in optimization techniques (linear programming, integer programming). Strong Python or R programming skills. SQL expertise for large, complex datasets. Strong communication skills with the ability to partner with business stakeholders. Preferred Experience in Retail, Restaurant, and/or Convenience Stores a plus. Experience with cloud platforms (Snowflake, AWS, GCP, Azure). Knowledge of BI tools (Tableau, Power BI, Looker). Physical Requirements Prolonged periods sitting/standing at a desk and working on a computer Must be able to lift up to 50 pounds Parker's is an equal opportunity employer committed to hiring a diverse workforce and sustaining an inclusive culture. Parker's does not discriminate on the basis of disability, veteran status or any other basis protected under federal, state, or local laws.

Company: Toorak Capital Partners is an integrated correspondent lending and table funding platform that acquires business purpose residential, multifamily and mixed-use loans throughout the U.S. and the United Kingdom. Headquartered in Tampa, FL., Toorak Capital Partners acquires these loans directly from a network of private lenders on a correspondent basis. Summary: The role of the Lead Data Engineer is to develop, implement, for building high performance, scalable data solution to support Toorak's Data Strategy Lead Data architecture for Toorak Capital. Lead efforts to create API framework to use data across customer facing and back office applications. Establish consistent data standards, reference architectures, patterns, and practices across the organization for both OLTP and OLAP (Data warehouse, Data Lake house) MDM and AI / ML technologies Lead sourcing and synthesis of Data Standardization and Semantics discovery efforts turning insights into actionable strategies that will define the priorities for the team and rally stakeholders to the vision Lead the data integration and mapping efforts to harmonize data. Champion standards, guidelines, and direction for ontology, data modeling, semantics and Data Standardization in general at Toorak. Lead strategies and design solutions for a wide variety of use cases like Data Migration (end-to-end ETL process), database optimization, and data architectural solutions for Analytics Data Projects Required Skills: Designing and maintaining the data models, including conceptual, logical, and physical data models 5+ years of experience using NoSQL systems like MongoDB, DynamoDB and Relational SQL Database systems (PostgreSQL) and Athena 5+ years of experience on Data Pipeline development, ETL and processing of structured and unstructured data 5+ years of experience in large scale real-time stream processing using Apache Flink or Apache Spark with messaging infrastructure like Kafka/Pulsar Proficiency in using data management tools and platforms, such as data cataloging software, data quality tools), and data governance platforms Experience with Big Query, SQL Mesh(or similar SQL-based cloud platform). Knowledge of cloud platforms and technologies such as Google Cloud Platform, Amazon Web Services. Strong SQL skills. Experience with API development and frameworks. Knowledge in designing solutions with Data Quality, Data Lineage, and Data Catalogs Strong background in Data Science, Machine Learning, NLP, Text processing of large data sets Experience in one or more of the following: Dataiku, DataRobot, Databricks, UiPath would be nice to have. Using version control systems (e.g., Git) to manage changes to data governance policies, procedures, and documentation Ability to rapidly comprehend changes to key business processes and the impact on overall Data framework. Flexibility to adjust to multiple demands, shifting priorities, ambiguity, and rapid change. Advanced analytical skills. High level of organization and attention to detail. Self-starter attitude with the ability to work independently. Knowledge of legal, compliance, and regulatory issues impacting data. Experience in finance preferred.

Full-time Description Job Title: Data Scientist III - Imaging & Omics Data Lead Job Type: Full-time Revised: 8/18/2025 Dynanet started with a focus on IT infrastructure and operations, helping organizations enhance their networks and overcome the limitations of 1990s technology. From strengthening communication channels to introducing innovative ways to collaborate and share information, Dynanet played a crucial role in shaping the early stages of digital transformation. The company's efforts helped organizations build the very fabric of connectivity that now powers our modern world. Over the last three decades, Dynanet has grown into a trusted partner for organizations looking to innovate boldly and transform seamlessly. While technology continues to evolve and unlock new opportunities, for nearly 30 years, Dynanet remains committed to delivering cutting-edge solutions that drive lasting change for its customers. Through agility, foresight, and an unwavering dedication to excellence, Dynanet continues to empower organizations to thrive in a rapidly changing digital landscape. Our story is more than just a story of technology - it's a story of vision, growth, and transformation that has shaped the past and continues to pave the way for the future. About the Role: This position supports a multi-institutional research initiative within the Computational Microscopy Imaging Lab (CMIL) focused on integrating digital pathology, spatial omics, and clinical datasets into an AI-enabled modeling platform. The Data Scientist III - Imaging & Omics Lead is responsible for developing analytic workflows that extract features from histology images and spatial molecular assays. This includes leading data processing, quality control, and harmonization efforts for tissue and omics data streams, and ensuring their reproducible integration into research pipelines. Requirements Roles & Responsibilities: ESSENTIAL FUNCTIONS OF THE JOB AND THE PERCENTAGE OF TIME SPENT ON EACH FUNCTION: Imaging and Omics Pipeline Development - 35% Design and implement data pipelines for histopathology and spatial omics sources (e.g., spatial transcriptomics, CODEX). Apply image processing, segmentation, and normalization techniques using Python-based libraries. Ensure pipelines are reproducible and version-controlled to meet analytic standards. Feature Extraction and Model Input Generation - 25% Use deep learning and statistical approaches to extract meaningful features from tissue images and molecular assays. Generate structured representations suitable for integration with AI/ML models. Collaborate with model developers to align feature formats with input requirements. Data Harmonization and Quality Assurance - 20% Coordinate with institutional collaborators to harmonize data formats, metadata, and preprocessing standards. Conduct QC reviews, troubleshoot data artifacts, and document all analytic transformations. Ensure compatibility between imaging/omics data and other project modalities. Documentation and Cross-Team Collaboration - 15% Maintain technical documentation for workflows and codebases. Participate in project meetings, share updates, and contribute to team deliverables. Support communication of imaging and omics data workflows to non-technical collaborators. Mentorship and Innovation Support - 5% Provide informal guidance to student researchers or junior analysts. Recommend new tools or analytic methods to improve pipeline performance MARGINAL FUNCTIONS OF THE JOB AND THE PERCENTAGE OF TIME SPENT ON EACH FUNCTION Technical Reporting and Communication - 5% Contribute to documentation for manuscripts, presentations, and project deliverables by summarizing imaging/omics pipeline components. Assist with visualization or slide preparation for updates to stakeholders or funders. Tool Evaluation and Pipeline Optimization - 5% Investigate emerging analytic tools or frameworks relevant to image and omics data. Test and recommend integration of tools that enhance processing speed, reproducibility, or analytic depth. Dynanet Team Requirements and Expectations: Possess Strong written and verbal communication skills. Highly organized with an ability to prioritize, balance, and effectively advance multiple competing priorities in a high-volume, fast-paced environment. Ability to interact in a professional and collaborative manner with fellow Dynanet Teammates and the clients, and business partners that we work with. Ability and desire to challenge and educate yourself to support and advance IT services delivery in the Federal agencies we serve. Excellent judgment and creative problem-solving skills. Respond to team member and client requests via email, MS teams, or other communication means during core business hours. Active listening skills to understand clients' needs, and collaboration skills to work with other developers and designers. Education/Experience Requirements: Master's degree in bioinformatics, biomedical engineering, computer science, data science, or a related field and three years of relevant experience; or a doctoral degree and one year of experience. Experience with digital pathology or spatial omics data (e.g., Visium, CODEX, MIBI). Proficiency in Python and image analysis libraries (e.g., OpenCV, scikit-image, MONAI). Familiarity with ML/AI workflows and model input preparation. Experience working in collaborative, interdisciplinary research environments. Strong documentation and data provenance tracking skills. Employee Benefits Overview: Industry Competitive Compensation Medical and Dental Insurance Paid Time Off/Holidays 401(k) Retirement Plans with Matching Paid Training Employee Referral Program Employee Development Program

The UF Health - Precision Health Research Center (PHRC) located in The Villages, FL, hosted within the Clinical and Translational Science Institute (CTSI) seeks an enthusiastic and qualified individual to fill the Data Scientist IV position. This position will work with the PHRC Director as part of the leadership team to develop, implement, and coordinate data management in translational and implementation science research projects aimed at improving health care quality, outcomes and well-being for older adults. The Data Scientist IV at the PHRC will be responsible for selecting and applying appropriate analytical methods to answer questions and test hypotheses as specified by clinical researchers, administrators and clinicians. This position will require expertise in both database design and complex statistical methods and algorithms. Expected projects will include design of research and operational databases and statistical analyses, and development of reporting infrastructures. Providing leadership to domain experts on issues related to principles of data science and analytical methods. Prioritizing and coordinating multiple tasks so as to achieve tight deadlines (as determined by commitments to funding agencies), and complying in a timely manner with administrative requests and requirements. More About This Role Data Processing Analytics This position will utilize data science and statistical software such as Python, R, and SAS, to analyze and interpret research data. This position will also use other database/analytical software platforms (e.g., MSSQL) to develop queries and manipulate data for deployment to real-time systems used in data activities. Expertise will be necessary to design and develop scripts to transform data from multiple data sources into primary data collection centers and make the data analytical-ready. Additional expertise in software such as RedCap and databases will be important for success. Knowledge and expertise will be needed in integrating, filtering and extracting multivariate and multimodal clinical databases for patient cohorts of interest from local databases and data warehouses. Administration of Projects This position will be responsible for formulating procedures for effective administration of research projects and protection of health information in accordance with University policy, and all applicable state and federal laws. This position will also be responsible for ensuring quality, consistency and validity of large multimodal datasets. Writing Reports of Analyses

Working Title: Internship Salary: To Be Determined by the Agency Data Science Internship State of Florida Opportunities are located throughout Florida Internship Overview and Responsibilities: The State of Florida is seeking motivated individuals to join our workforce. Our agencies are looking for bright, highly motivated college students and recent graduates to participate in a unique opportunity to gain experience firsthand in the operations of state government while obtaining valuable on-the-job training. As a data science intern, responsibilities may include the following: * Leverage tools to interpret data sets; paying particular attention to trends and patterns that could be valuable for diagnostic and predictive analytics efforts. * Collaborate with cross-functional teams to understand data needs and deliver data-driven solutions. * Assist with the maintenance, ongoing support, and reporting for automation across the agency. * Assist in collecting, cleaning, and preprocessing structured and unstructured datasets from various sources. * Support exploratory data analysis to uncover trends, patterns, and insights. * Contribute to the improvement of data quality, data governance, and metadata standards. * Conduct research on emerging tools, techniques, and technologies. Applications are accepted year-round. Internships may be paid or unpaid and there is no guarantee of employment. Knowledge, Skills, and Abilities: * Knowledge of data analytics methodologies and tools. * Ability to work independently as well as with others. * Knowledge of data modeling, data mining and data cleansing techniques; and data analysis. * Knowledge of automation and application of automation tools. * Ability to prioritize tasks, meet deadlines, and manage time effectively. * Knowledge of statistics & statistical modeling. * Ability to collect, evaluate, and prioritize automation opportunities. * Proven ability to work ethically and with integrity. Minimum Qualifications: * Must be currently enrolled or graduated within the last twelve months from an accredited college or university degree program. * Working knowledge of database systems and querying languages (e.g., SQL) to extract and manipulate data efficiently. The State of Florida is an Equal Opportunity Employer/Affirmative Action Employer, and does not tolerate discrimination or violence in the workplace. Candidates requiring a reasonable accommodation, as defined by the Americans with Disabilities Act, must notify the agency hiring authority and/or People First Service Center (***************. Notification to the hiring authority must be made in advance to allow sufficient time to provide the accommodation. The State of Florida supports a Drug-Free workplace. All employees are subject to reasonable suspicion drug testing in accordance with Section 112.0455, F.S., Drug-Free Workplace Act. Location:

Job DescriptionDescription: The Senior Data Engineer will lead the design, development, and optimization of OCP's cloud-based data architecture in Azure. This role is accountable for building scalable, automated data pipelines, integrating diverse clinical, financial, and operational data sources, and ensuring data quality and consistency across the enterprise. The Senior Data Engineer sets technical standards, drives innovation in automation, and positions OCP to scale as the organization grows through acquisitions and additional data sources. Key Responsibilities Pipeline Architecture & Development Design and maintain scalable ETL/ELT pipelines using Azure Data Factory, Synapse, and Data Lake. Develop reusable ingestion and transformation frameworks to onboard new practices and acquisitions with minimal downtime. Engineer high-performance solutions for large, complex data sets, balancing batch and real-time ingestion. Optimize workflows to reduce latency, improve resiliency, and control cloud costs. Cloud Platform Leadership Own the technical design and ongoing evolution of OCP's Azure-based data environment. Define and enforce standards for architecture, storage, and orchestration to ensure enterprise-grade scalability. Partner with infrastructure and security leaders to align architecture with compliance, resiliency, and disaster recovery requirements. Anticipate growth and design data environments to accommodate new systems, acquisitions, and emerging technologies. Data Integration & Modeling Integrate diverse data sources including EHR, practice management, financials, clinical, marketing, and HR systems. Develop and maintain dimensional and semantic models that support enterprise-wide reporting and analytics. Partner with business and clinical stakeholders to ensure models align with operational and strategic needs. Enable analysts and business teams by delivering clean, well-structured data sets that reduce manual manipulation. Data Quality, Security & Governance Implement automated monitoring and validation to proactively identify and resolve data quality issues. Collaborate with governance leaders to define standardized metrics, rules, and master data across divisions. Maintain transparency through documentation of all data flows, transformations, and dependencies. Enforce HIPAA, privacy, and security controls across pipelines and environments. Collaboration, Leadership & Innovation Mentor junior engineers and analysts, providing technical guidance and code reviews. Serve as subject matter expert for data engineering best practices, tool selection, and performance tuning. Collaborate with analytics, finance, operations, and clinical leaders to prioritize and deliver new capabilities. Continuously evaluate new Azure capabilities, open-source tools, and automation techniques to advance OCP's data maturity. Requirements: Preferred Qualifications Experience working with healthcare data (EHR, claims, financial, clinical outcomes). Familiarity with Power BI data modeling and semantic layer integration. Exposure to advanced Azure capabilities (Databricks, machine learning pipelines, streaming architectures). Proven experience driving data governance and compliance practices in healthcare or regulated environments. Physical Requirements: Ability to sit and work at a computer for extended periods. Occasional light lifting of office equipment (e.g., laptop, monitors) if needed. Occasional travel to market locations or corporate offices may be required. Compliance: Adhere to all internal safety, security, and confidentiality standards. Maintain full compliance with HIPAA and other regulatory frameworks.

•Review, verify and analyze insurance data. •Assist is the development and implementation of sound rates and/or rating plans. •Assist in the development and pricing of new products. •Assist in preparing regulatory filings. •Effectively gather and compile data. Evaluate data to ensure data integrity and identify discrepancies.Complete analysis of data and summarize results •Develop reports needed by senior management and other business units to monitor progress in improving profitability and implementation of business. •Provide technical support to other business units. •Review, verify and analyze insurance data. •Assist is the development and implementation of sound rates and/or rating plans. •Assist in the development and pricing of new products. •Assist in preparing regulatory filings. •Effectively gather and compile data. Evaluate data to ensure data integrity and identify discrepancies.Complete analysis of data and summarize results •Develop reports needed by senior management and other business units to monitor progress in improving profitability and implementation of business. •Provide technical support to other business units. •Review, verify and analyze insurance data. •Assist is the development and implementation of sound rates and/or rating plans. •Assist in the development and pricing of new products. •Assist in preparing regulatory filings. •Effectively gather and compile data. Evaluate data to ensure data integrity and identify discrepancies.Complete analysis of data and summarize results •Develop reports needed by senior management and other business units to monitor progress in improving profitability and implementation of business. •Provide technical support to other business units. Skills & Requirements •Review, verify and analyze insurance data. •Assist is the development and implementation of sound rates and/or rating plans. •Assist in the development and pricing of new products. •Assist in preparing regulatory filings. •Effectively gather and compile data. Evaluate data to ensure data integrity and identify discrepancies.Complete analysis of data and summarize results •Develop reports needed by senior management and other business units to monitor progress in improving profitability and implementation of business. •Provide technical support to other business units.

SYSRS IT Services specializes in offering IT Services: Technology Services, Consulting Services, Software Solutions and Applications. Incorporated in 2013, SYSRS IT Services focuses on innovative and practical delivery of services to meet the critical IT missions of its clients. At SYSRS IT Services, we are committed to serving our customers with a wide range of information technology services and solutions with guaranteed satisfaction, friendly and professional service, during convenient hours of operation, and resulting in a great onsite/offsite experience. Job Requisition: Sr. Data Analytics Engineer Job Description: Leidos is seeking a Senior Data Analytics Engineer to develop a new data analytics platform service offering for a federal client. You will contribute to establishing the ingestion patterns, data storage patterns, data transformation methods, and data lake formation. You'll support data architecture-related activities through business needs analysis and routine issue resolution, including data pipeline design and data lake solution design. Put your consulting expertise to use to drive our future Data Analytics platform. Primary Responsibilities: Develop future state data architecture in consultation and alignment with the enterprise architecture team. Help the architecture team put together conceptual, logical, and physical data architecture and define the technical roadmap to the future state. Design data warehouse/data marts/data lakes/data hubs solutions and work with various data warehouse technologies to develop plans that best support the Program. In collaboration with technical leads and subject matter experts (SME), develop and manage architecture framework and design patterns of data analytics, integration, and visualization platform as per standards and industry best practices. Ability to analyze and evaluate new products as it relates to data lake/processing/analytics and suggest platform architecture modifications as necessary Participate in customer meetings to review business requirements and maintain the traceability of data sources and artifacts. Support data migration from the current state to the future state platform. Provide technical guidance and consultation and clarify technical and business requirements to development teams. Translate business needs into enterprise data architecture requirements and identify and forecast future state data architecture alternatives. Experiment with cloud-native, serverless tools and advise on new tools to determine optimal solutions given the requirements dictated by the use case. Expert in both traditional and modern data architecture and processing concepts, including relational databases, data warehousing, big data, NoSQL, and business analytics Show efficiency in handling data - tracking data lineage, ensuring data quality, and improving discoverability of data. Ability and desire to conduct hands-on data tool development work to complete proofs of concept Provide periodic briefings to peers and leadership on the state of the data architecture. Ability to multitask, problem-solving skills, and customer management skills are required. Ability and desire to work with other program staff and customers to reach design decisions within given constraints Qualifications Basic Qualifications: Candidate must have bachelor's or master's degree with prior relevant experience. Must have 8+ years of Data Analytics experience. Experience in data pipeline architecture design, development, and optimization. Working experience or familiarity with AWS data analytics tools like Redshift, EMR, Data Lake Formation, AWS Glue, AWS Glue Brew, AWS Athena, Lambda, AWS Data Pipeline, Cognito, Quicksight, and S3. Experience with a variety of database technologies: RDBMS, NoSQL, search, data lakes. Experience with one or more visualization tools such as Power BI, Tableau, and Qlik. Additional Information Preferred Qualifications: Experience with AWS-specific data management and analytics strategies. Experience doing trade analysis on multiple data analytics tooling options supporting data lake and visualization layer.

# Job Description: AI Task Evaluation & Statistical Analysis Specialist ## Role Overview We're seeking a data-driven analyst to conduct comprehensive failure analysis on AI agent performance across finance-sector tasks. You'll identify patterns, root causes, and systemic issues in our evaluation framework by analyzing task performance across multiple dimensions (task types, file types, criteria, etc.). ## Key Responsibilities - **Statistical Failure Analysis**: Identify patterns in AI agent failures across task components (prompts, rubrics, templates, file types, tags) - **Root Cause Analysis**: Determine whether failures stem from task design, rubric clarity, file complexity, or agent limitations - **Dimension Analysis**: Analyze performance variations across finance sub-domains, file types, and task categories - **Reporting & Visualization**: Create dashboards and reports highlighting failure clusters, edge cases, and improvement opportunities - **Quality Framework**: Recommend improvements to task design, rubric structure, and evaluation criteria based on statistical findings - **Stakeholder Communication**: Present insights to data labeling experts and technical teams ## Required Qualifications - **Statistical Expertise**: Strong foundation in statistical analysis, hypothesis testing, and pattern recognition - **Programming**: Proficiency in Python (pandas, scipy, matplotlib/seaborn) or R for data analysis - **Data Analysis**: Experience with exploratory data analysis and creating actionable insights from complex datasets - **AI/ML Familiarity**: Understanding of LLM evaluation methods and quality metrics - **Tools**: Comfortable working with Excel, data visualization tools (Tableau/Looker), and SQL ## Preferred Qualifications - Experience with AI/ML model evaluation or quality assurance - Background in finance or willingness to learn finance domain concepts - Experience with multi-dimensional failure analysis - Familiarity with benchmark datasets and evaluation frameworks - 2-4 years of relevant experience

Classification Title: Data Scientist III Classification Minimum Requirements: A Bachelor's Degree in data science, statistics, bioinformatics, analytics, or similar field and five years of experience; Master's Degree in data science, statistics, bioinformatics, analytics, or similar field and three years of experience; Doctoral Degree in data science, statistics, bioinformatics, analytics, or similar field and one year of experience. Job Description: The Department of Medicine, Division of Nephrology Quantitative Health is seeking a full time Data Scientist III. This position supports a multi-institutional, NIH-funded research initiative within the Computational Microscopy Imaging Lab (CMIL) focused on integrating digital pathology, spatial omics, and clinical datasets into an AI-enabled modeling platform. The Data Scientist III - Imaging & Omics Lead is responsible for developing analytic workflows that extract features from histology images and spatial molecular assays. This includes leading data processing, quality control, and harmonization efforts for tissue and omics data streams, and ensuring their reproducible integration into research pipelines. The position reports to Dr. Pinaki Sarder, Principal Investigator. Essential functions; Imaging and Omics Pipeline Development - * Design and implement data pipelines for histopathology and spatial omics sources (e.g., spatial transcriptomics, CODEX). * Apply image processing, segmentation, and normalization techniques using Python-based libraries. * Ensure pipelines are reproducible and version-controlled to meet analytic standards. Feature Extraction and Model Input Generation - * Use deep learning and statistical approaches to extract meaningful features from tissue images and molecular assays. * Generate structured representations suitable for integration with AI/ML models. * Collaborate with model developers to align feature formats with input requirements. Data Harmonization and Quality Assurance - * Coordinate with institutional collaborators to harmonize data formats, metadata, and preprocessing standards. * Conduct QC reviews, troubleshoot data artifacts, and document all analytic transformations. * Ensure compatibility between imaging/omics data and other project modalities. Documentation and Cross-Team Collaboration - * Maintain technical documentation for workflows and codebases. * Participate in project meetings, share updates, and contribute to team deliverables. * Support communication of imaging and omics data workflows to non-technical collaborators. Mentorship and Innovation Support - * Provide informal guidance to student researchers or junior analysts. * Recommend new tools or analytic methods to improve pipeline performance

Working Title: Internship Salary: To Be Determined by the Agency Data Science Internship State of Florida Opportunities are located throughout Florida Internship Overview and Responsibilities: The State of Florida is seeking motivated individuals to join our workforce. Our agencies are looking for bright, highly motivated college students and recent graduates to participate in a unique opportunity to gain experience firsthand in the operations of state government while obtaining valuable on-the-job training. As a data science intern, responsibilities may include the following: * Leverage tools to interpret data sets; paying particular attention to trends and patterns that could be valuable for diagnostic and predictive analytics efforts. * Collaborate with cross-functional teams to understand data needs and deliver data-driven solutions. * Assist with the maintenance, ongoing support, and reporting for automation across the agency. * Assist in collecting, cleaning, and preprocessing structured and unstructured datasets from various sources. * Support exploratory data analysis to uncover trends, patterns, and insights. * Contribute to the improvement of data quality, data governance, and metadata standards. * Conduct research on emerging tools, techniques, and technologies. Applications are accepted year-round. Internships may be paid or unpaid and there is no guarantee of employment. Knowledge, Skills, and Abilities: * Knowledge of data analytics methodologies and tools. * Ability to work independently as well as with others. * Knowledge of data modeling, data mining and data cleansing techniques; and data analysis. * Knowledge of automation and application of automation tools. * Ability to prioritize tasks, meet deadlines, and manage time effectively. * Knowledge of statistics & statistical modeling. * Ability to collect, evaluate, and prioritize automation opportunities. * Proven ability to work ethically and with integrity. Minimum Qualifications: * Must be currently enrolled or graduated within the last twelve months from an accredited college or university degree program. * Working knowledge of database systems and querying languages (e.g., SQL) to extract and manipulate data efficiently. The State of Florida is an Equal Opportunity Employer/Affirmative Action Employer, and does not tolerate discrimination or violence in the workplace. Candidates requiring a reasonable accommodation, as defined by the Americans with Disabilities Act, must notify the agency hiring authority and/or People First Service Center (***************. Notification to the hiring authority must be made in advance to allow sufficient time to provide the accommodation. The State of Florida supports a Drug-Free workplace. All employees are subject to reasonable suspicion drug testing in accordance with Section 112.0455, F.S., Drug-Free Workplace Act. Location:

**1\. Role Overview**Mercor is seeking applied data science professionals to support a strategic analytics initiative with a global enterprise. This contract-based opportunity focuses on extracting insights, building statistical models, and informing business decisions through advanced data science techniques. Freelancers will translate complex datasets into actionable outcomes using tools like Python, SQL, and visualization platforms. This short-term engagement emphasizes experimentation, modeling, and stakeholder communication - distinct from production ML engineering. **2\. Key Responsibilities** ● Translate business questions into data science problems and analytical workflows ● Conduct data wrangling, exploratory analysis, and hypothesis testing ● Develop statistical models and predictive tools for decision support ● Create compelling data visualizations and dashboards for business users ● Present findings and recommendations to non-technical stakeholders **3\. Ideal Qualifications** ● 5+ years of applied data science or analytics experience in business settings ● Proficiency in Python or R (pandas, NumPy, Jupyter) and strong SQL skills ● Experience with data visualization tools (e.g., Tableau, Power BI) ● Solid understanding of statistical modeling, experimentation, and A/B testing ● Strong communication skills for translating technical work into strategic insights **4\. More About the Opportunity** ● Remote ● **Expected commitment: min 30 hours/week ● Project duration: ~6 weeks** **5\. Compensation & Contract Terms** ● $75-100/hour ● Paid weekly via Stripe Connect ● You'll be classified as an independent contractor **6\. Application Process** ● Submit your resume followed by domain expertise interview and short form **7.About Mercor** ● Mercor is a talent marketplace that connects top experts with leading AI labs and research organizations ● Our investors include Benchmark, General Catalyst, Adam D'Angelo, Larry Summers, and Jack Dorsey ● Thousands of professionals across domains like law, creatives, engineering, and research have joined Mercor to work on frontier projects shaping the next era of AI

# Job Description: AI Task Evaluation & Statistical Analysis Specialist ## Role Overview We're seeking a data-driven analyst to conduct comprehensive failure analysis on AI agent performance across finance-sector tasks. You'll identify patterns, root causes, and systemic issues in our evaluation framework by analyzing task performance across multiple dimensions (task types, file types, criteria, etc.). ## Key Responsibilities - **Statistical Failure Analysis**: Identify patterns in AI agent failures across task components (prompts, rubrics, templates, file types, tags) - **Root Cause Analysis**: Determine whether failures stem from task design, rubric clarity, file complexity, or agent limitations - **Dimension Analysis**: Analyze performance variations across finance sub-domains, file types, and task categories - **Reporting & Visualization**: Create dashboards and reports highlighting failure clusters, edge cases, and improvement opportunities - **Quality Framework**: Recommend improvements to task design, rubric structure, and evaluation criteria based on statistical findings - **Stakeholder Communication**: Present insights to data labeling experts and technical teams ## Required Qualifications - **Statistical Expertise**: Strong foundation in statistical analysis, hypothesis testing, and pattern recognition - **Programming**: Proficiency in Python (pandas, scipy, matplotlib/seaborn) or R for data analysis - **Data Analysis**: Experience with exploratory data analysis and creating actionable insights from complex datasets - **AI/ML Familiarity**: Understanding of LLM evaluation methods and quality metrics - **Tools**: Comfortable working with Excel, data visualization tools (Tableau/Looker), and SQL ## Preferred Qualifications - Experience with AI/ML model evaluation or quality assurance - Background in finance or willingness to learn finance domain concepts - Experience with multi-dimensional failure analysis - Familiarity with benchmark datasets and evaluation frameworks - 2-4 years of relevant experience

# Job Description: AI Task Evaluation & Statistical Analysis Specialist ## Role Overview We're seeking a data-driven analyst to conduct comprehensive failure analysis on AI agent performance across finance-sector tasks. You'll identify patterns, root causes, and systemic issues in our evaluation framework by analyzing task performance across multiple dimensions (task types, file types, criteria, etc.). ## Key Responsibilities - **Statistical Failure Analysis**: Identify patterns in AI agent failures across task components (prompts, rubrics, templates, file types, tags) - **Root Cause Analysis**: Determine whether failures stem from task design, rubric clarity, file complexity, or agent limitations - **Dimension Analysis**: Analyze performance variations across finance sub-domains, file types, and task categories - **Reporting & Visualization**: Create dashboards and reports highlighting failure clusters, edge cases, and improvement opportunities - **Quality Framework**: Recommend improvements to task design, rubric structure, and evaluation criteria based on statistical findings - **Stakeholder Communication**: Present insights to data labeling experts and technical teams ## Required Qualifications - **Statistical Expertise**: Strong foundation in statistical analysis, hypothesis testing, and pattern recognition - **Programming**: Proficiency in Python (pandas, scipy, matplotlib/seaborn) or R for data analysis - **Data Analysis**: Experience with exploratory data analysis and creating actionable insights from complex datasets - **AI/ML Familiarity**: Understanding of LLM evaluation methods and quality metrics - **Tools**: Comfortable working with Excel, data visualization tools (Tableau/Looker), and SQL ## Preferred Qualifications - Experience with AI/ML model evaluation or quality assurance - Background in finance or willingness to learn finance domain concepts - Experience with multi-dimensional failure analysis - Familiarity with benchmark datasets and evaluation frameworks - 2-4 years of relevant experience

**1\. Role Overview**Mercor is seeking applied data science professionals to support a strategic analytics initiative with a global enterprise. This contract-based opportunity focuses on extracting insights, building statistical models, and informing business decisions through advanced data science techniques. Freelancers will translate complex datasets into actionable outcomes using tools like Python, SQL, and visualization platforms. This short-term engagement emphasizes experimentation, modeling, and stakeholder communication - distinct from production ML engineering. **2\. Key Responsibilities** ● Translate business questions into data science problems and analytical workflows ● Conduct data wrangling, exploratory analysis, and hypothesis testing ● Develop statistical models and predictive tools for decision support ● Create compelling data visualizations and dashboards for business users ● Present findings and recommendations to non-technical stakeholders **3\. Ideal Qualifications** ● 5+ years of applied data science or analytics experience in business settings ● Proficiency in Python or R (pandas, NumPy, Jupyter) and strong SQL skills ● Experience with data visualization tools (e.g., Tableau, Power BI) ● Solid understanding of statistical modeling, experimentation, and A/B testing ● Strong communication skills for translating technical work into strategic insights **4\. More About the Opportunity** ● Remote ● **Expected commitment: min 30 hours/week ● Project duration: ~6 weeks** **5\. Compensation & Contract Terms** ● $75-100/hour ● Paid weekly via Stripe Connect ● You'll be classified as an independent contractor **6\. Application Process** ● Submit your resume followed by domain expertise interview and short form **7.About Mercor** ● Mercor is a talent marketplace that connects top experts with leading AI labs and research organizations ● Our investors include Benchmark, General Catalyst, Adam D'Angelo, Larry Summers, and Jack Dorsey ● Thousands of professionals across domains like law, creatives, engineering, and research have joined Mercor to work on frontier projects shaping the next era of AI

# Job Description: AI Task Evaluation & Statistical Analysis Specialist ## Role Overview We're seeking a data-driven analyst to conduct comprehensive failure analysis on AI agent performance across finance-sector tasks. You'll identify patterns, root causes, and systemic issues in our evaluation framework by analyzing task performance across multiple dimensions (task types, file types, criteria, etc.). ## Key Responsibilities - **Statistical Failure Analysis**: Identify patterns in AI agent failures across task components (prompts, rubrics, templates, file types, tags) - **Root Cause Analysis**: Determine whether failures stem from task design, rubric clarity, file complexity, or agent limitations - **Dimension Analysis**: Analyze performance variations across finance sub-domains, file types, and task categories - **Reporting & Visualization**: Create dashboards and reports highlighting failure clusters, edge cases, and improvement opportunities - **Quality Framework**: Recommend improvements to task design, rubric structure, and evaluation criteria based on statistical findings - **Stakeholder Communication**: Present insights to data labeling experts and technical teams ## Required Qualifications - **Statistical Expertise**: Strong foundation in statistical analysis, hypothesis testing, and pattern recognition - **Programming**: Proficiency in Python (pandas, scipy, matplotlib/seaborn) or R for data analysis - **Data Analysis**: Experience with exploratory data analysis and creating actionable insights from complex datasets - **AI/ML Familiarity**: Understanding of LLM evaluation methods and quality metrics - **Tools**: Comfortable working with Excel, data visualization tools (Tableau/Looker), and SQL ## Preferred Qualifications - Experience with AI/ML model evaluation or quality assurance - Background in finance or willingness to learn finance domain concepts - Experience with multi-dimensional failure analysis - Familiarity with benchmark datasets and evaluation frameworks - 2-4 years of relevant experience

**1\. Role Overview**Mercor is seeking applied data science professionals to support a strategic analytics initiative with a global enterprise. This contract-based opportunity focuses on extracting insights, building statistical models, and informing business decisions through advanced data science techniques. Freelancers will translate complex datasets into actionable outcomes using tools like Python, SQL, and visualization platforms. This short-term engagement emphasizes experimentation, modeling, and stakeholder communication - distinct from production ML engineering. **2\. Key Responsibilities** ● Translate business questions into data science problems and analytical workflows ● Conduct data wrangling, exploratory analysis, and hypothesis testing ● Develop statistical models and predictive tools for decision support ● Create compelling data visualizations and dashboards for business users ● Present findings and recommendations to non-technical stakeholders **3\. Ideal Qualifications** ● 5+ years of applied data science or analytics experience in business settings ● Proficiency in Python or R (pandas, NumPy, Jupyter) and strong SQL skills ● Experience with data visualization tools (e.g., Tableau, Power BI) ● Solid understanding of statistical modeling, experimentation, and A/B testing ● Strong communication skills for translating technical work into strategic insights **4\. More About the Opportunity** ● Remote ● **Expected commitment: min 30 hours/week ● Project duration: ~6 weeks** **5\. Compensation & Contract Terms** ● $75-100/hour ● Paid weekly via Stripe Connect ● You'll be classified as an independent contractor **6\. Application Process** ● Submit your resume followed by domain expertise interview and short form **7.About Mercor** ● Mercor is a talent marketplace that connects top experts with leading AI labs and research organizations ● Our investors include Benchmark, General Catalyst, Adam D'Angelo, Larry Summers, and Jack Dorsey ● Thousands of professionals across domains like law, creatives, engineering, and research have joined Mercor to work on frontier projects shaping the next era of AI

**1\. Role Overview**Mercor is seeking applied data science professionals to support a strategic analytics initiative with a global enterprise. This contract-based opportunity focuses on extracting insights, building statistical models, and informing business decisions through advanced data science techniques. Freelancers will translate complex datasets into actionable outcomes using tools like Python, SQL, and visualization platforms. This short-term engagement emphasizes experimentation, modeling, and stakeholder communication - distinct from production ML engineering. **2\. Key Responsibilities** ● Translate business questions into data science problems and analytical workflows ● Conduct data wrangling, exploratory analysis, and hypothesis testing ● Develop statistical models and predictive tools for decision support ● Create compelling data visualizations and dashboards for business users ● Present findings and recommendations to non-technical stakeholders **3\. Ideal Qualifications** ● 5+ years of applied data science or analytics experience in business settings ● Proficiency in Python or R (pandas, NumPy, Jupyter) and strong SQL skills ● Experience with data visualization tools (e.g., Tableau, Power BI) ● Solid understanding of statistical modeling, experimentation, and A/B testing ● Strong communication skills for translating technical work into strategic insights **4\. More About the Opportunity** ● Remote ● **Expected commitment: min 30 hours/week ● Project duration: ~6 weeks** **5\. Compensation & Contract Terms** ● $75-100/hour ● Paid weekly via Stripe Connect ● You'll be classified as an independent contractor **6\. Application Process** ● Submit your resume followed by domain expertise interview and short form **7.About Mercor** ● Mercor is a talent marketplace that connects top experts with leading AI labs and research organizations ● Our investors include Benchmark, General Catalyst, Adam D'Angelo, Larry Summers, and Jack Dorsey ● Thousands of professionals across domains like law, creatives, engineering, and research have joined Mercor to work on frontier projects shaping the next era of AI

**1\. Role Overview**Mercor is seeking applied data science professionals to support a strategic analytics initiative with a global enterprise. This contract-based opportunity focuses on extracting insights, building statistical models, and informing business decisions through advanced data science techniques. Freelancers will translate complex datasets into actionable outcomes using tools like Python, SQL, and visualization platforms. This short-term engagement emphasizes experimentation, modeling, and stakeholder communication - distinct from production ML engineering. **2\. Key Responsibilities** ● Translate business questions into data science problems and analytical workflows ● Conduct data wrangling, exploratory analysis, and hypothesis testing ● Develop statistical models and predictive tools for decision support ● Create compelling data visualizations and dashboards for business users ● Present findings and recommendations to non-technical stakeholders **3\. Ideal Qualifications** ● 5+ years of applied data science or analytics experience in business settings ● Proficiency in Python or R (pandas, NumPy, Jupyter) and strong SQL skills ● Experience with data visualization tools (e.g., Tableau, Power BI) ● Solid understanding of statistical modeling, experimentation, and A/B testing ● Strong communication skills for translating technical work into strategic insights **4\. More About the Opportunity** ● Remote ● **Expected commitment: min 30 hours/week ● Project duration: ~6 weeks** **5\. Compensation & Contract Terms** ● $75-100/hour ● Paid weekly via Stripe Connect ● You'll be classified as an independent contractor **6\. Application Process** ● Submit your resume followed by domain expertise interview and short form **7.About Mercor** ● Mercor is a talent marketplace that connects top experts with leading AI labs and research organizations ● Our investors include Benchmark, General Catalyst, Adam D'Angelo, Larry Summers, and Jack Dorsey ● Thousands of professionals across domains like law, creatives, engineering, and research have joined Mercor to work on frontier projects shaping the next era of AI