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Applied Intelligence Jobs in Florida (NOW HIRING)

FL · On-site

Transitioning from passive reporting to proactive intelligence, you will derive and champion data ... Experience: 4 to 6 years of applied experience in digital analytics, performance marketing analysis ...

FL · On-site

Transitioning from passive reporting to proactive intelligence, you will derive and champion data ... Experience: 4 to 6 years of applied experience in digital analytics, performance marketing analysis ...

Showing results 21-40

Applied Intelligence information

See Florida salary details

$34K

$78.2K

$107.6K

How much do applied intelligence jobs pay per year?

As of Aug 22, 2026, the average yearly pay for applied intelligence in Florida is $78,199.00, according to ZipRecruiter salary data. Most workers in this role earn between $70,200.00 and $88,600.00 per year, depending on experience, location, and employer.

What is an applied intelligence?

An Applied Intelligence job focuses on leveraging data, analytics, AI, and automation to solve business challenges and drive decision-making. Professionals in this role work with advanced technologies to analyze trends, optimize processes, and improve efficiency. They collaborate with teams across various industries to develop data-driven strategies and innovative solutions. Typical responsibilities may include machine learning model development, data visualization, and business intelligence reporting. This role is ideal for individuals with strong analytical, problem-solving, and technical skills.

What are the typical projects and responsibilities for an applied intelligence role?

In an Applied Intelligence role, you will typically work on projects that involve analyzing large datasets, developing predictive models, and generating actionable insights to solve real business challenges. Daily responsibilities may include collaborating with cross-functional teams, building dashboards and reports, and presenting findings to stakeholders. You'll often partner closely with IT, marketing, operations, and executive leadership to ensure that data-driven recommendations align with organizational objectives. This role offers exposure to various industries and processes, making it ideal for those interested in both analytics and business strategy. Over time, strong performers can advance to leadership positions or specialized roles in data science or business analytics.

What are the key skills and qualifications needed to thrive in the applied intelligence position, and why are they important?

To thrive as an Applied Intelligence professional, you need a strong background in data analytics, problem-solving, and business strategy, often with a degree in computer science, engineering, or a related field. Familiarity with data analysis tools (like SQL, Python, R), business intelligence platforms (such as Power BI or Tableau), and certifications in analytics or project management are commonly required. Excellent communication, adaptability, and collaborative skills are essential to translate complex insights into actionable business solutions. These skills are crucial for effectively driving data-driven initiatives that help organizations achieve strategic goals.

Infographic showing various Applied Intelligence job openings in Florida as of August 2026, with employment types broken down into 88% Full Time, 9% Part Time, and 3% Contract. Highlights an 82% Physical, 5% Hybrid, and 13% Remote job distribution, with an average salary of $78,199 per year, or $37.6 per hour.

Data Science & Business Intelligence Analyst

blueteam

Boca Raton, FL • On-site

$90 - $130/hr

Other

Posted 8 days ago


Job description

Position:Data Science & Business Intelligence Analyst

Location: Boca Raton, FL

Job Id:355

# of Openings:1

Job Title: Data Science & Business Intelligence Analyst

Department: Corporate

Reports To: President

Location: Boca Raton, FL (in-office position; not remote or hybrid)

FLSA Status: Exempt

Company Summary

BlueTeam is a US-based provider of national disaster recovery, remediation, reconstruction, renovation, and roofing services for commercial properties. Our core business focuses on cleanup and mitigation efforts for recovery from fire damage, roof leaks, flooding, pipe bursts, and post-disaster remediation due to severe weather. We exclusively serve commercial sectors including hospitality, senior housing, healthcare, commercial offices, municipalities, multifamily living, and institutional markets.

SUMMARY:

The Data Science & Business Intelligence Analyst serves as the company's primary quantitative resource, transforming data from project, financial, and customer systems into decisions leadership can act on. The role spans the full analytical range: data acquisition and modeling, recurring and ad hoc reporting, statistical and predictive modeling, and the applied use of artificial intelligence to extract structured information from the document-heavy workflows that drive this business.

The analyst will work with structured and unstructured data, build and maintain the reporting layer, develop forecasting and predictive models, validate those models against actual results, and automate manual processes. The standard for this role is defensibility: every number produced must reconcile to its source system, and every model must be documented, tested against data it was not trained on, and explainable to a non-technical audience. Selecting the simplest method that answers the question is preferred over sophistication for its own sake.

This position supports the executive team crossing all departments of the Company. Initial priorities will center on sales reporting, expanding to enterprise analytics as the reporting foundation matures.

ESSENTIAL DUTIES AND RESPONSIBILITIES:
  • Collect, clean, validate, and transform data from multiple source systems, including project management, accounting, CRM, and field data collection platforms.
  • Develop dashboards, reports, and visualizations that provide actionable insights.
  • Analyze historical trends, operational performance, productivity metrics, and business outcomes, including job‑level margin, estimate versus actual variance, backlog and pipeline conversion, win rates by client and business unit, and receivable aging and collection cycle time.
  • Create recurring and ad hoc reporting for leadership teams.
  • Identify patterns, risks, and opportunities through quantitative analysis.
  • Build and maintain the queries, extracts, and pipelines that feed the reporting layer, including API‑based extraction from source systems.
  • Reconcile reporting to the general ledger and to source systems so that analytical output and financial reporting do not diverge.
Data Science, Statistics & Predictive Analytics
  • Build forecasting models for revenue, backlog conversion, labor and equipment demand, and cash flow, accounting for the seasonality and catastrophe‑driven volatility inherent to storm restoration work.
  • Design and interpret experiments, quantify statistical significance, and measure realized business impact against forecast.
  • Present quantitative findings with stated confidence, known limitations, and the reasoning behind method selection.
  • Apply large language model tooling to production analytical workflows, including structured data extraction from unstructured documents, classification, and summarization, rather than ad hoc manual prompting alone.
  • Develop AI‑assisted processes to streamline reporting, research, document review, and decision support, with human review controls at each output stage.
  • Evaluate emerging AI capabilities and recommend practical business applications, including build versus buy assessment and cost per unit of output.
  • Build automated workflows that reduce manual effort and increase efficiency
Data Management & Governance
  • Ensure data accuracy, integrity, and consistency across reporting systems.
  • Support data governance initiatives, validation processes, and data quality improvements.
  • Partner with stakeholders to establish reporting standards and best practices.
  • Document data sources, transformations, model logic, and code so that all work is reproducible by someone other than the author.
Cross‑Functional Collaboration
  • Partner with business leaders to understand strategic priorities and deliver data‑driven recommendations.
  • Present findings to both technical and non‑technical audiences.
  • Support initiatives across Sales, Operations, Finance, Marketing, and Executive Leadership.
  • Translate complex analyses into actionable business recommendations.
  • Challenge analytically unsupported conclusions, including those already held by leadership, and state plainly where available data is insufficient to answer the question asked.
QUALIFICATIONS:
  • 5 years of progressive experience in data analytics, data science, business intelligence, or a related quantitative field, including hands‑on ownership of both reporting and predictive modeling work.
  • Strong analytical and problem‑solving skills with experience interpreting large datasets.
  • SQL proficiency sufficient to write and optimize multi‑table joins, aggregations, and window functions against a production database without assistance.
  • Working proficiency in Python or R for data manipulation, statistical analysis, and modeling (for example pandas, scikit‑learn, stats models, or equivalent libraries).
  • Demonstrated experience building, validating, and putting into use at least one forecasting or predictive model that informed an operating decision.
  • Expert proficiency in Excel, including advanced formulas, pivot tables, dynamic financial and operational models, and AI‑assisted model development.
  • Proficiency in CRM platforms, with hands‑on experience across multiple systems; ability to navigate, maintain data integrity, and extract insights across different systems environments.
  • Proficiency in Power BI, including dashboard design, DAX formulas, and data modeling.
  • Working proficiency with current AI tooling applied to real analytical work, including prompt design, structured output, and validation of AI‑generated results before use.
  • Excellent communication skills with the ability to translate data into clear insights.
Preferred Qualifications
  • Background in construction, restoration, insurance, or another project‑based industry is not required but is a plus.
  • Experience building automated dashboards and reporting systems.
  • Demonstrated ability to use AI for prospect and client research, including synthesizing information from multiple sources into actionable sales intelligence and executive‑ready presentations.
  • Experience with cloud data platforms and pipeline orchestration
  • Experience with large language model APIs, retrieval methods, embeddings, and evaluation techniques.
EDUCATION and/or EXPERIENCE:
  • Bachelor's degree in statistics, mathematics, economics, data science, computer science, engineering, business analytics, or another quantitative discipline.
PHYSICAL DEMANDS:

While performing the duties of this job, the employee is regularly required to type and look at a computer screen for long periods of the day. The employee must be able to sit for long periods of time. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

QUALIFICATIONS: To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements listed above are representative of the knowledge, skill, and/or ability required.

NOTE: This job description is not designed to cover or contain a comprehensive listing of activities, duties or responsibilities that are required of the employee for this job. Duties, responsibilities and activities may change at any time with or without notice. BBMK Contracting, LLC dba BlueTeam (BlueTeam) is a Drug Free Workplace as well as an Equal Opportunity Employer. Qualified applicants shall be considered for all positions without regard to race, color, sex, religion, national origin, age, disability, veteran status, or any other status

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