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Freelance Data Analyst Ai Jobs (NOW HIRING)

Alignerr

Financial Analyst AI Researcher - Remote

$50 - $100/hr

Cross-reference narrative disclosures with underlying quantitative data * Summarize financial ... Freelance autonomy with the structure of meaningful, task-based work * Put your financial expertise ...

Kforce Technology Staffing

AI/Data Analyst

Riviera Beach, FL · On-site

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Kforce has a client that is seeking an AI/Data Analyst in Riviera Beach, FL. Summary: The project that they are doing is taking global schedule (schedule of everything they have to build across the ...

Mindrift

Freelance Data Scraping Engineer (Python)

$37/hr

Our mission is to help develop high-quality AI technologies by combining real-world expertise from ... About the Role This is a freelance role for a Tendem project. As a Python Data Scraping Engineer ...

Randstad Digital

AI / ML Data Analyst

Charlotte, NC · On-site

$40.70 - $50.70/hr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

We are seeking a highly motivated Data Analyst with strong analytical skills and practical knowledge of Artificial Intelligence (AI), Machine Learning (ML), and Data Analytics to transform data into ...

New

Solomon Page

Data Analyst

Austin, TX · On-site

$35 - $45/hr

  • Medical

  • Dental

  • Retirement

We are seeking a skilled Data Analyst to perform complex data analysis supporting both ad-hoc and ... freelancers - which sets us apart in the industries we serve. About Solomon Page Founded in 1990 ...

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How much do freelance data analyst ai jobs pay per year?

As of Aug 13, 2026, the average yearly pay for freelance data analyst ai in the United States is $82,640.00, according to ZipRecruiter salary data. Most workers in this role earn between $62,500.00 and $97,000.00 per year, depending on experience, location, and employer.

What is the difference between Freelance Data Analyst Ai vs Freelance Data Scientist?

AspectFreelance Data Analyst AiFreelance Data Scientist
CredentialsTypically requires a degree in data analysis, statistics, or related fields; certifications like Microsoft Certified Data Analyst are commonOften requires advanced degrees (Master's or PhD) in data science, statistics, or related areas; certifications like Certified Data Scientist are beneficial
Work EnvironmentFreelance projects often involve data cleaning, visualization, and basic modeling for clients across industriesFreelance roles focus on complex modeling, machine learning, and predictive analytics for diverse sectors
Industry UsageUsed across finance, marketing, healthcare, and e-commerce for data reporting and insightsApplied in AI development, predictive modeling, and advanced analytics in tech, finance, and research

While both roles involve data analysis, Freelance Data Analyst Ai primarily focuses on data visualization and reporting, whereas Freelance Data Scientist handles complex modeling and machine learning. The choice depends on your expertise and project needs.

What is a freelance data analyst ai?

Freelance Data Analyst AI professionals are independent experts who utilize artificial intelligence techniques to analyze and interpret complex data sets for various clients or organizations. They use tools like machine learning, data mining, and statistical analysis to extract valuable insights that help businesses make data-driven decisions. Unlike in-house analysts, freelancers work on a project-by-project basis, offering flexibility and specialized skills tailored to client needs.

What are the key skills and qualifications needed to thrive as a freelance data analyst ai?

To thrive as a Freelance Data Analyst AI, you need strong analytical skills, proficiency in statistics, and a solid understanding of data modeling and machine learning, often supported by a degree in a quantitative field. Familiarity with tools such as Python, R, SQL, and data visualization platforms, as well as knowledge of AI frameworks like TensorFlow or PyTorch, is essential. Excellent communication, problem-solving abilities, and self-motivation help you stand out when managing client projects independently. These skills and qualities are crucial for delivering accurate insights, meeting client needs, and staying competitive in a fast-evolving field.

How do freelance data analyst ai professionals typically manage client expectations and project timelines?

Freelance Data Analyst AI professionals often work with multiple clients simultaneously, making clear communication and expectation management vital. They usually start by defining project scopes, deliverables, and timelines in detail, often through contracts or statements of work. Regular updates and progress reports help maintain transparency and address any potential roadblocks early. Utilizing project management tools and setting realistic deadlines can also help freelancers balance workloads and ensure timely delivery while maintaining quality. This proactive approach not only builds trust but also increases the likelihood of repeat business and positive referrals.
More about Freelance Data Analyst Ai jobs
What cities are hiring for Freelance Data Analyst Ai jobs? Cities with the most Freelance Data Analyst Ai job openings:
What are the most commonly searched types of Data Analyst Ai jobs? The most popular types of Data Analyst Ai jobs are:
What states have the most Freelance Data Analyst Ai jobs? States with the most job openings for Freelance Data Analyst Ai jobs include:
What job categories do people searching Freelance Data Analyst Ai jobs look for? The top searched job categories for Freelance Data Analyst Ai jobs are:
Freelance Data Analyst Ai jobs near you
Infographic showing various Freelance Data Analyst Ai job openings in the United States as of August 2026, with employment types broken down into 60% Full Time, and 40% Contract. Highlights an 100% In-person job distribution, with an average salary of $82,640 per year, or $39.7 per hour.

Data and AI Project Analyst

DPR Construction

Monroe, LA • On-site

Full-time

Re-posted 19 days ago

DPR Construction rating

8.0

Company rating: 8.0 out of 10

Based on 37 frontline employees who took The Breakroom Quiz

18th of 80 rated construction

Job description

Job Description
Overview
The Data & AI Project Analyst serves as the field-facing connector between project teams, account leadership, owners/JV partners, and DPR's Technology & Innovation groups-translating business needs into scalable data, analytics, integration, and AI solutions. This role engages early to shape requirements, standardize approaches across projects, coordinate delivery with U.S. and offsite teams, and ensure all data sharing and AI use aligns with governance, legal, and contractual obligations. This is a jobsite-based role, which will require regular travel between all jobsites within a national account.
Data & Development
  • Engage early in pursuit and preconstruction to:
    • Identify owner-mandated technologies
    • Capture data requirements and reporting obligations
    • Surface integration needs and constraints
    • AI opportunity identification
  • Partner with:
    • Integration Managers
    • Account Leadership
    • Project Teams to align on scalable and repeatable approaches
    • Other Account leads
    • Other T&I Groups - (CT, IT, ETS)
  • Align project-level data needs with DPR's Data Strategy and enterprise standards, delivering consistent, flexible solutions that drive measurable impact across the account.
  • Translate business and project needs into clear data, analytics, and integration requirements.
  • This role is primarily field-based, with approximately 75% of time spent on active jobsites and limited opportunity for remote work. This includes participation in key meetings and workgroup meetings at the jobsite.
  • Align AI use cases with owner expectations and contract constraints
  • Advise on feasibility and value of AI-driven solutions

Data & Integration Enablement
  • Influence strategic technology decisions related to data, analytics, AI, and development.
  • Lead conversations with owners, JV partners, and stakeholders on data exchange approaches, including:
    • System access vs data sharing
    • File-based vs platform-based integrations
    • Reporting vs operational use cases
    • Guiding the team through custom analytics and development.
  • Responsible for coordination with Data Engineering, Solution Architecture, Analytics and offsite teams to:
    • Define integration approaches
    • Ensure feasibility and scalability, avoiding one-off or unsustainable solutions
    • Act as a Funnel for requests with US and Offsite teams
  • Manage UAT and QA/QC for deliverables, collaborating with U.S. and offsite teams to incorporate feedback, and own final production readiness and quality.
  • Drive data readiness and integration strategies to support scalable pipelines and enable effective consumption of predictive and generative AI models.
  • Support implementation of standardized data exchange frameworks and templates
  • Ensure all external data sharing aligns with data governance, legal, and contractual requirements
  • Provide hands-on support in analytics and Power BI, iterating on reports, making minor updates, and developing proof-of-concept solutions based on real-time user feedback.

Intake, Prioritization & Coordination
  • Act as the front door for data and development requests at the account level
  • Work with Data & Development Lead - Mega Projects for the prioritization across the accounts
  • Ensure requests are:
    • Clearly defined
    • Properly scoped
    • Prioritized based on business impact
  • Coordinate execution across:
    • Data Engineering
    • Data Analytics
    • AI/ML
    • Software Development
  • Add AI-specific intake criteria (value, risk, data readiness)
  • Prioritize AI initiatives alongside analytics and development work
  • Coordinate across AI/ML teams for model development and deployment
  • Track progress, manage expectations, and communicate updates to stakeholders
  • Escalate risks, conflicts, and capacity constraints when needed

Standardization & Reuse
  • Identify opportunities to:
    • Reuse existing dashboards, pipelines, and integrations
    • Avoid duplication across projects and accounts
  • Promote standardized approaches for:
    • Data mapping
    • Integration patterns
    • Reporting structures
    • Drive implementation of AI use cases by prioritizing reusable models, prompts, and workflows, and minimizing one-off, non-scalable solutions.
  • Contribute to the development of templates and best practices for mega projects.

Project Onboarding & Enablement
  • Support setup of new projects by:
    • Aligning on data requirements and integrations
    • Facilitating access to systems and tools
    • Coordinating onboarding workflows (data, analytics, reporting)
    • Work with Integration Managers to understand account-level and project-level technology stacks including:
      • DPR standard tools
      • Owner-mandated systems
      • JV partner systems
      • AI/ML tools, platforms, and model usage
      • Track approved vs non-approved AI technologies
      • Identify implications of introducing AI into project tech stacks
  • Partner with Integration Managers to deliver and support project landing pages, access management workflows, standardized setup processes, and effective analytics storytelling for project teams.
  • Facilitate rollout of dashboards and tools, including training and enablement for internal and external project teams for onboarding, access, and effective data usage.
  • Champion the use of existing tools and platforms across project teams to drive consistency and maximize value.
  • Assess the technology stack and identify deviations from standards, evaluating downstream impacts on data, development, AI, integrations, cost, and support.

Data Governance & Compliance
  • Ensure all data activities align with:
    • DPR data governance policies
    • NDA & Contractual obligations
    • Client data requirements
    • Ensure AI usage complies with client data restrictions and contracts
    • Align with AI governance policies (data privacy, model usage, vendor constraints)
  • Help define:
    • What data can be shared
    • How it can be used (internal vs external)
    • Where it should be stored (e.g., warehouse-first approach)
  • Support documentation of:
    • Data definitions
    • Data sources
    • Integration logic

Technical Skills
  • Working knowledge of Data and AI
    • Basic understanding of AI/ML and their capabilities
    • Data gathering and quality issues
    • Power BI
  • Business process and systems thinking
    • Map workflows and identify inefficiencies
    • Understand system dependencies
  • Support integration of AI into existing DPR workflows and systems, from adoption to deployment
  • Ability to assist with piloting AI and data solutions on projects, gather user feedback, identify adoption barriers, and refine workflows to ensure tools deliver real-world value.
  • Maintain a working knowledge of AI, data capabilities, and limitations to evaluate opportunities realistically. Ask critical questions about data availability, problem fit, and automation value while leveraging common tools such as dashboards and reporting platforms.

Qualifications
  • Minimum of 4 years of experience in a relevant data analytics/integration delivery role with a strong Power BI background and experience in the construction industry.
  • Proven track record of managing stakeholder expectations and delivering data solutions aligned with business priorities.
  • Experience with modern data platforms like Snowflake and Microsoft Fabric.
  • Experience with mapping, documenting, and analyzing business workflows to identify inefficiencies and gaps.
  • Ability to translate ambiguous project team requests into clear, actionable use cases with defined data sources and success criteria.
  • Strong problem-solving skills and ability to troubleshoot complex data issues.
  • Excellent communication skills, with the ability to work collaboratively in a team environment.
  • Experience working with or coordinating with overseas teams is a strong plus

DPR Construction is a forward-thinking, self-performing general contractor specializing in technically complex and sustainable projects for the advanced technology, life sciences, healthcare, higher education and commercial markets. Founded in 1990, DPR is a great story of entrepreneurial success as a private, employee-owned company that has grown into a multi-billion-dollar family of companies with offices around the world.
Working at DPR, you'll have the chance to try new things, explore paths and shape your future. Here, we build opportunity together-by harnessing our talents, enabling curiosity and pursuing our collective ambition to make the best ideas happen. We are proud to be recognized as a great place to work by our talented teammates and leading news organizations like U.S. News and World Report, Forbes, Fast Company and Newsweek.
Explore our open opportunities at www.dpr.com/careers.

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