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Data Analyst Computer Science Jobs in Boca Raton, FL

Kforce Technology Staffing

Data Engineer

Fort Lauderdale, FL · On-site

$109K - $131K/yr

A Bachelor's degree in Computer Science, Data Science, Business Analytics, or a related field is ideal * 7+ years as a Report Writer, Data Analyst, or in a similar role focused on report development ...

ADT Security Services

Data Architect

Boca Raton, FL · On-site

$60.25 - $77.50/hr

Collaborate with product owners, data engineers, data analysts, data scientists, and other ... A bachelor's degree in computer science, engineering, or a related field, or an equivalent amount ...

Varsity Tutors

Data Science Tutor

Miramar, FL · Remote

$18 - $40/hr

What We Look For In a Data Science Tutor * Advanced Subject Mastery ... Deep knowledge of statistical analysis, data wrangling, exploratory data analysis, machine learning ...

Varsity Tutors

Data Science Tutor

Cooper City, FL · Remote

$18 - $40/hr

What We Look For In a Data Science Tutor * Advanced Subject Mastery ... Deep knowledge of statistical analysis, data wrangling, exploratory data analysis, machine learning ...

Varsity Tutors

Data Science Tutor

Sunrise, FL · Remote

$18 - $40/hr

What We Look For In a Data Science Tutor * Advanced Subject Mastery ... Deep knowledge of statistical analysis, data wrangling, exploratory data analysis, machine learning ...

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Data Analyst Computer Science information

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$32.3K

$78.4K

$129.1K

How much do data analyst computer science jobs pay per year?

As of Jul 11, 2026, the average yearly pay for data analyst computer science in Boca Raton, FL is $78,423.00, according to ZipRecruiter salary data. Most workers in this role earn between $59,300.00 and $92,000.00 per year, depending on experience, location, and employer.

Is 40 too late for data science?

Data analysts and data scientists can successfully transition into the field at age 40 or older, as skills in programming, statistics, and data visualization are valuable regardless of age. Many professionals acquire relevant certifications or learn tools like Python, R, or SQL later in their careers to enhance their prospects.

What are the key skills and qualifications needed to thrive as a Data Analyst in Computer Science, and why are they important?

To thrive as a Data Analyst in Computer Science, you need strong analytical skills, proficiency in statistics, and a relevant degree in computer science, mathematics, or a related field. Familiarity with data analysis tools such as SQL, Python, R, and data visualization platforms like Tableau or Power BI, as well as experience with database systems, are typically required. Attention to detail, problem-solving abilities, and effective communication help data analysts translate complex data into actionable insights for stakeholders. These skills are crucial for accurately interpreting data trends, supporting business decisions, and driving organizational growth.

What is a Data Analyst in Computer Science?

A Data Analyst in Computer Science is a professional who collects, processes, and analyzes data to help organizations make informed decisions. They use various statistical tools and programming languages, such as Python, R, and SQL, to interpret complex datasets and identify trends or patterns. Their work often involves cleaning data, creating visualizations, and preparing reports for stakeholders. Data Analysts play a key role in turning raw data into actionable insights that drive business strategies.

How does a Data Analyst with a computer science background typically collaborate with other departments within a company?

Data Analysts with a computer science background often work closely with teams such as marketing, product development, and IT to translate raw data into actionable insights. They may participate in cross-functional meetings to understand business goals, provide data-driven recommendations, and help automate data collection processes. Strong communication skills are essential, as analysts must explain technical findings in a way that non-technical stakeholders can understand. This collaborative environment not only broadens their impact but also exposes them to various aspects of the business, fostering professional growth.

Can I be a data analyst with computer science?

Yes, a background in computer science provides a strong foundation for a data analyst role, as it covers programming, data structures, and algorithms. Data analysts often use tools like SQL, Excel, and statistical software, and having programming skills in languages such as Python or R is highly beneficial.

Is a data analyst a high salary?

Data analysts typically earn competitive salaries that vary based on experience, location, and industry. In general, they have higher-than-average starting pay compared to many entry-level roles, especially when skilled in tools like Excel, SQL, and data visualization software. Advanced skills or certifications can lead to higher compensation.

Will AI replace a data analyst?

AI can automate routine data processing and basic analysis tasks, but data analysts are essential for interpreting complex data, making strategic decisions, and providing context. The role of a data analyst involves skills like critical thinking, domain knowledge, and communication, which are difficult for AI to fully replicate. Therefore, AI is more likely to augment rather than replace data analysts in the foreseeable future.
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Data Analyst Computer Science jobs near you
Senior Data Analyst, Energy Preconstruction

Senior Data Analyst, Energy Preconstruction

Moss

Fort Lauderdale, FL • On-site

$82K - $103K/yr

Full-time

Re-posted 20 days ago

Job description

COMPANY OVERVIEW
Moss is a national, privately held construction firm providing innovative solutions resulting in award-winning projects. With regional offices across the United States, Moss focuses on construction management, energy EPC, and design-build. The company's diverse portfolio encompasses a wide range of sectors, including luxury high-rise residential, landmark mixed-use developments, hospitality, K-12 and higher education, justice, solar energy and battery storage, and sports. Moss is ranked by Engineering News-Record as the nation's top solar contractor and one of the top 50 general contractors. Moss prides itself on a strong entrepreneurial culture that honors safety, quality, client engagement, and employee development. Its employees consistently rank Moss as one of the best places to work.
POSITION SCOPE AND ORGANIZATIONAL IMPACT
Moss' Senior Data Analyst plays a critical role in transforming fragmented data across projects, engineering, cost, productivity, procurement, and performance into structured, actionable insights that enhance estimating accuracy, mitigate risk, and drive profitability within the Energy Preconstruction team. This role will lead to the development of a reliable historical dataset that supports benchmarking, conceptual pricing, forecasting, and strategic decision-making.
Working with limited oversight, this individual will partner across preconstruction, procurement, finance, engineering, and IT to help create a single source of truth for preconstruction data. Through data cleansing, multi-system querying, dashboard development, and business analysis, this role will strengthen bid strategy, improve estimate confidence, identify cost and risk patterns, and support the long-term growth of a dedicated data function within Energy Preconstruction.
ESSENTIAL JOB DUTIES AND RESPONSIBILITIES
  • Cleanse, normalize, validate, and consolidate historical data on estimating, engineering, cost, productivity, procurement, project parameters, and project performance from spreadsheets, takeoff files, ERP/CRM systems, and other legacy sources.
  • Build, maintain, and improve structured historical datasets and databases that support estimating benchmarks, conceptual pricing, root cause analysis, and future predictive modeling.
  • Improve data quality and usability by resolving inconsistencies in naming conventions, units of measure, metadata, assumptions, and source traceability.
  • Build and run queries against internal databases and enterprise systems; use SQL and other tools to extract, join, filter, validate, and organize data from multiple sources.
  • Develop repeatable query logic and data pipelines that improve accessibility, consistency, and auditability, while partnering with IT and data teams to align with governance standards and future data architecture.
  • Identify correlations, trends, anomalies, and performance patterns across historical and active energy projects, including relationships among design variables, cost drivers, labor productivity, procurement timing, geography, weather, and project outcomes.
  • Generate insights that improve profitability, reduce risk, strengthen conceptual estimates, and support value engineering and broader business decision-making.
  • Benchmark current bids and conceptual estimates against historical project performance, market trends, prior wins, and known cost drivers; support the Indicative Lead and PCM in pricing and repricing exercises through structured data analysis.
  • Build dashboards, reports, and KPI visibility tools using Power BI or similar platforms to track estimate accuracy, cost variance, margin trends, bid competitiveness, win rates, and project milestones.
  • Translate complex analysis into clear, decision-oriented reporting for leadership and business stakeholders.
  • Support risk analysis, forecasting, sensitivity analysis, scenario modeling, contingency planning, and feasibility analysis using internal and external data, including location, weather, irradiance, and grid proximity.
  • Support the improvement and standardization of estimating and engineering templates, define and reinforce data standards, act as a technical liaison across estimating, engineering, procurement, finance, and IT, and contribute to continuous improvement and future system integration.
  • Perform other duties as assigned.

EDUCATION AND WORK EXPERIENCE
  • Bachelor's degree in Data Analytics, Data Science, Engineering, Finance, Information Systems, or a related field is required.
  • 5+ years of experience in data analytics or a related analytical role is required.
  • Strong experience in cleansing, standardizing, and structuring complex datasets is required.
  • Strong SQL proficiency and experience querying databases are required.
  • Strong Excel proficiency is required; advanced Excel skills, including Power Query, PivotTables, and structured data manipulation, are preferred.
  • Strong experience building dashboards and reports in Power BI or a similar tool is required.
  • Experience in identifying correlations, patterns, and trends in data to support business decisions is required.
  • Experience working independently and collaborating across business and technical functions is required.
  • Experience supporting data governance, standardization, or system integration efforts is required.
  • Knowledge of data quality, database concepts, query logic, enterprise data environments, dashboarding, KPI development, benchmarking, correlation analysis, trend analysis, and forecasting is required.
  • Strong analytical, problem-solving, documentation, communication, and stakeholder collaboration skills are required.
  • Experience in energy, EPC, construction, or infrastructure environments is preferred.
  • Experience with ERP systems, such as Oracle, and CRM systems is preferred.
  • Experience with Python or R for data analysis or automation is preferred.
  • Familiarity with estimating, engineering, and procurement workflows is preferred.

JOB TITLE: SENIOR DATA ANALYST, ENERGY PRECONSTRUCTION
JOB LOCATION: FORT LAUDERDALE, FL
CLASSIFICATION: FULL TIME - EXEMPT - SALARIED
REPORTS TO: SENIOR MANAGER, SOLAR ESTIMATING
Moss is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.

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