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Python Data Analyst Jobs in Tampa, FL (NOW HIRING)

Lincare Holdings, Inc.

Data Scientist

Clearwater, FL

... Python. Through the combination of statistical knowledge, AI skills and technical coding languages, a data scientist will be required to complete any assigned analytical projects in a timely and ...

Inizio Partners

Data Engineer - Healthcare

Tampa, FL · Remote

$108K - $129K/yr

Collaborate with cross-functional stakeholders including data analysts, clinicians, operations teams, and software engineers Required Skills & Experience * Strong hands-on experience with Python for ...

Raymondjames

Data Quality Analyst

Saint Petersburg, FL · On-site

Concepts of business analytics and familiarity with business intelligence tools such as Python, Tableau, Qlik, MS Power BI, MS Teams, SharePoint, etc. * Experience in using data gap remediation and ...

Citi

Data Scientist Assistant Vice President

Tampa, FL · On-site

... Python, machine learning, and statistical analysis, combined with strong business acumen and the ... Lead all phases of the data science project lifecycle, including requirements gathering, data ...

SynergisticIT

Software engineer

Tampa, FL · On-site

Currently, We are looking for entry-level software programmers, IT enthusiasts, Python/Java developers, Data analysts/ Data Scientists. We welcome candidates with all visas and citizens to apply. Who ...

Citi

Senior Python Developer - Vice President

Tampa, FL

$114K - $154K/yr

Strong analytical, logical, systems thinking, and critical analysis skills. * Excellent written and ... Big Data Technologies (Apache Spark, Hadoop, Kafka) and data warehousing. * Frontend Development ...

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All JobsPython Data Analyst JobsPython Data Analyst Jobs in Tampa, FL

Python Data Analyst information

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$32.1K

$78.1K

$128.5K

How much do python data analyst jobs pay per year?

As of Jun 23, 2026, the average yearly pay for python data analyst in Tampa, FL is $78,096.00, according to ZipRecruiter salary data. Most workers in this role earn between $59,100.00 and $91,700.00 per year, depending on experience, location, and employer.

What does a Python Data Analyst do?

A Python Data Analyst leverages the Python programming language to collect, process, and analyze large sets of data. They use tools and libraries like Pandas, NumPy, and Matplotlib to clean data, perform statistical analysis, and create visualizations that help organizations make data-driven decisions. Their role often involves extracting insights from complex datasets, automating data workflows, and communicating findings to stakeholders through reports or dashboards. Python Data Analysts play a crucial part in turning raw data into actionable business intelligence.

How do Python Data Analysts typically collaborate with other departments within an organization?

Python Data Analysts often work closely with teams such as marketing, finance, and product development to provide data-driven insights that inform business decisions. They regularly participate in cross-functional meetings to understand departmental objectives, gather requirements for data analysis, and present their findings in an accessible manner. Effective communication and the ability to translate technical results into actionable recommendations are essential, as analysts often act as a bridge between technical data and non-technical stakeholders.

What is the difference between Python Data Analyst vs Data Scientist?

AspectPython Data AnalystData Scientist
Required SkillsPython, SQL, data visualization, statistical analysisPython, R, machine learning, statistical modeling
Work EnvironmentBusiness analytics, reporting, data cleaningAdvanced modeling, predictive analytics, research
Industry UsageFinance, marketing, healthcare, retailTech, finance, research, AI development

While both roles require Python and data analysis skills, Data Scientists typically engage in more complex modeling and machine learning, whereas Python Data Analysts focus on data cleaning, visualization, and reporting to support business decisions.

What Does a Python Data Analyst Do?

As a Python data analyst, you use the Python programming language to develop tools for data mining, analysis, and data visualization. You typically develop a script to meet the specific data needs of your client or employer. Then, you test your code and perform debugging duties before deploying it in a live environment. Some data analysts also have algorithm creation responsibilities. In this case, after creating and testing an algorithm, you use Python with your algorithm to interpret data. You also develop reports to show to your clients or employers, and you may code a web app or interface that clients can use to visualize data sets.

Are Python coders still in demand?

Python data analysts are currently in high demand due to the language's versatility in data analysis, machine learning, and automation. Skills in libraries like Pandas, NumPy, and experience with data visualization tools increase employability across various industries.

Is 40 too old to become a data analyst?

Age is not a barrier to becoming a data analyst. Many professionals successfully transition into data analysis at various ages by acquiring skills in programming languages like Python or SQL, and gaining experience with data visualization tools. Employers value skills and experience over age, and continuous learning can help you stay competitive in the field.

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

To thrive as a Python Data Analyst, you need strong analytical skills, a solid grasp of statistics, and proficiency in Python programming, often supported by a degree in data science, mathematics, or a related field. Familiarity with data analysis libraries like pandas and NumPy, visualization tools such as Matplotlib or Seaborn, and experience with data querying languages like SQL are typically required. Attention to detail, critical thinking, and effective communication help you derive insights and present findings clearly to stakeholders. These skills and qualities are vital for transforming raw data into actionable business intelligence and supporting data-driven decision-making.

Is Python useful for data analysts?

Python is highly useful for data analysts as it offers powerful libraries like Pandas, NumPy, and Matplotlib for data manipulation, analysis, and visualization. It is widely used in the industry for automating tasks, building data pipelines, and performing statistical analysis, making it a valuable skill for the role.

Will AI replace data analysts?

AI is transforming the role of data analysts by automating routine tasks such as data cleaning and basic analysis, but it is unlikely to fully replace them. Data analysts are needed to interpret complex insights, make strategic decisions, and develop models that require domain expertise and critical thinking. Skills in programming, data visualization, and understanding AI tools remain valuable in this evolving field.
More about Python Data Analyst jobs
What are the most commonly searched types of Python Data Analyst jobs in Tampa, FL? The most popular types of Python Data Analyst jobs in Tampa, FL are:
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What job categories do people searching Python Data Analyst jobs in Tampa, FL look for? The top searched job categories for Python Data Analyst jobs in Tampa, FL are:
What cities near Tampa, FL are hiring for Python Data Analyst jobs? Cities near Tampa, FL with the most Python Data Analyst job openings:
Python Data Analyst jobs near you
Infographic showing various Python Data Analyst job openings in Tampa, FL as of June 2026, with employment types broken down into 3% As Needed, 33% Full Time, 53% Part Time, 10% Contract, and 1% Nights. Highlights an 82% Physical, 7% Hybrid, and 11% Remote job distribution, with an average salary of $78,096 per year, or $37.5 per hour.

Investment Data Scientist | Financial Modeling & Portfolio Analytics

Raymond James Financial, Inc.

Saint Petersburg, FL

Full-time

Posted 24 days ago

Job description

Job Description Summary
Job Description
As part of the AMS Research team, the Investment Data Scientist plays a key role in developing, improving, and evaluating quantitative models that directly support investment decision-making and portfolio management. This is a hands-on technical role focused on writing production-quality Python code to analyze financial datasets, enhance portfolio construction methods, and automate investment workflows.
You'll collaborate closely with Investment Committee members, analysts, and other stakeholders to improve the investment process through portfolio optimization, statistical modeling, and process automation. You'll also develop interactive dashboards and visualizations that translate complex analytical outputs into actionable insights. This role requires strong analytical thinking, the ability to solve complex technical problems independently and collaboratively, and a commitment to delivering high-quality, validated results.
Essential Duties and Responsibilities
  • Develop and maintain robust Python code for portfolio construction, statistical analysis, and automation of investment workflows.
  • Design and implement portfolio optimization algorithms.
  • Apply advanced statistical methods to extract insights from financial datasets.
  • Collaborate with Investment Committee members, analysts, and quant team members to align model development with investment objectives and operational needs.
  • Build automated processes to eliminate manual tasks, reduce errors, and improve workflow efficiency.
  • Create interactive dashboards and visualizations to communicate analytical findings.

Knowledge, Skills, and Abilities
Core Knowledge (Required):
  • Python libraries for data manipulation and array mathematics: pandas, NumPy, SciPy, and optimization libraries such as CVXPY.
  • Statistical modeling and optimization: mixed integer programming, regressions, time series, and Monte Carlo simulation.
  • Data visualization: Streamlit, Tableau, Power BI, Plotly Dash, or similar platforms.
  • Quantitative finance: portfolio construction methods, risk modeling, and financial data analysis.

Preferred Knowledge:
  • Financial markets, investment products, and portfolio theory.
  • Performance measurement and attribution methodologies.
  • Django framework for database management.
  • Advanced investment concepts and practices in the securities industry.

Technical Skills:
  • Writing clean, documented, and version-controlled Python code.
  • Translating business problems into quantitative models and technical solutions.
  • Building and maintaining automated workflows.
  • Creating clear, intuitive data visualizations for non-technical audiences.
  • Validating and testing models to ensure accuracy and reliability.
  • Performing performance calculations and financial data analysis.

Abilities:
  • Work independently and collaboratively in a fast-paced team environment.
  • Deliver accurate, high-quality analytical work through rigorous testing and validation.
  • Manage multiple projects with competing deadlines.
  • Communicate complex technical concepts clearly to non-technical stakeholders.
  • Debug code, validate results, and ensure analytical accuracy.
  • Balance attention to detail with strategic thinking.
  • Adapt to changing priorities and requirements.
  • Learn new quantitative techniques and investment concepts quickly.
  • Promote team effectiveness through knowledge sharing and collaboration.

Educational and Experience Requirements
  • Bachelor's degree in Computer Science, Mathematics, Statistics, Physics, Engineering, Economics, Finance, or a related quantitative field.
  • 3-6 years of hands-on experience with Python development and quantitative analysis.
  • Demonstrated experience building optimization models, statistical systems, and/or automated workflows.
    OR
  • Any equivalent combination of experience, education, and/or training approved by Human Resources.

Education
Bachelor's: Computer and Information Science, Bachelor's: Economics, Bachelor's: Engineering, Bachelor's: Finance, Bachelor's: Mathematics, Bachelor's: Physics, Bachelor's: Statistics
Work Experience
General Experience - 3 to 6 years
Certifications
Travel
Less than 25%
Workstyle
Hybrid
At Raymond James our associates use five guiding behaviors (Develop, Collaborate, Decide, Deliver, Improve) to deliver on the firm's core values of client-first, integrity, independence and a conservative, long-term view.
We expect our associates at all levels to:
• Grow professionally and inspire others to do the same
• Work with and through others to achieve desired outcomes
• Make prompt, pragmatic choices and act with the client in mind
• Take ownership and hold themselves and others accountable for delivering results that matter
• Contribute to the continuous evolution of the firm
At Raymond James - as part of our people-first culture, we honor, value, and respect the uniqueness, experiences, and backgrounds of all of our Associates. When associates bring their best authentic selves, our organization, clients, and communities thrive. The Company is an equal opportunity employer and makes all employment decisions on the basis of merit and business needs.

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