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Data Scientist Electrical Engineer Jobs in Florida

Establish and promote best practices in data science, machine learning, feature engineering, experimentation, model governance, and MLOps throughout the organization. * Stay current on industry ...

Data Scientist

Orlando, FL · On-site

$80 - $100/hr

Undergraduate degree in Data Science, Statistics, Mathematics, Computer Science, Engineering, or ... Strong programming skills in Python (e.g., Pandas, scikit-learn) and SQL * Experience with time ...

Data Science Location : Palm Beach , FL (Day One Onsite to Client Location) Experence : 8 + Years ... and feature engineering Experience with SQL (PostgreSQL, MySQL, BigQuery, Snowflake, etc ...

Collaborate with software engineers to bring the models to production environments. * Leverage AI ... Department Data Science Role Data Scientist Locations Fort Lauderdale, New York, NY, San Francisco ...

Expert Python developer using many different machine learning and data science frameworks including TensorFlow, PyTorch, Keras, Ray, RLLib, numpy/scipy, scikit-learn, Caffe, pandas, PyMC3, and ...

Required Qualifications Bachelor's degree in data science, Statistics, Computer Science, Mathematics, Engineering, Operations Research, Economics, or another quantitative or analytical discipline. TS ...

Data Scientist W2 Contract Location: hybrid - 3 days onsite, Orlando, FL Title: Data Scientist ... engineering, modeling, deployment, and monitoring * Develop production-ready solutions using ...

Data Scientist Schedule: Full-Time Shift: Day Job Travel: Yes - 10% of the time Minimum Clearance ... engineering, intelligence, and enterprise information technology markets. SAIC is Redefining ...

Master's degree in Data Science, Statistics, Computer Science, Econometrics, Data Analytics ... Strong programming experience with Python. * Strong SQL skills for data extraction, transformation ...

Master's degree in Data Science, Statistics, Computer Science, Econometrics, Data Analytics ... Strong programming experience with Python. * Strong SQL skills for data extraction, transformation ...

Master's degree in Data Science, Statistics, Computer Science, Econometrics, Data Analytics ... Strong programming experience with Python. * Strong SQL skills for data extraction, transformation ...

Master's degree in Data Science, Statistics, Computer Science, Econometrics, Data Analytics ... Strong programming experience with Python. * Strong SQL skills for data extraction, transformation ...

Master's degree in Data Science, Statistics, Computer Science, Econometrics, Data Analytics ... Strong programming experience with Python. * Strong SQL skills for data extraction, transformation ...

Master's degree in Data Science, Statistics, Computer Science, Econometrics, Data Analytics ... Strong programming experience with Python. * Strong SQL skills for data extraction, transformation ...

Master's degree in Data Science, Statistics, Computer Science, Econometrics, Data Analytics ... Strong programming experience with Python. * Strong SQL skills for data extraction, transformation ...

Master's degree in Data Science, Statistics, Computer Science, Econometrics, Data Analytics ... Strong programming experience with Python. * Strong SQL skills for data extraction, transformation ...

Master's degree in Data Science, Statistics, Computer Science, Econometrics, Data Analytics ... Strong programming experience with Python. * Strong SQL skills for data extraction, transformation ...

Showing results 41-60

Data Scientist Electrical Engineer information

What does a data scientist electrical engineer do?

A Data Scientist Electrical Engineer combines expertise in electrical engineering with advanced data analysis and machine learning skills. They analyze large sets of electrical data from systems such as power grids, electronic devices, or sensors to identify patterns, optimize performance, and predict failures. These professionals often work on smart grid technology, IoT applications, or improving the efficiency and reliability of electrical systems through data-driven insights. Their role bridges traditional engineering practices with modern data science techniques.

How does a data scientist electrical engineer typically collaborate with cross-functional teams to drive successful projects?

Data Scientist Electrical Engineers often work closely with hardware engineers, software developers, and data analytics teams to develop and optimize intelligent systems. Their role involves translating raw sensor or signal data into actionable insights through advanced analytics and machine learning models. Effective collaboration requires clear communication of complex technical findings and aligning analytical approaches with engineering constraints and project goals. This teamwork is essential for ensuring that data-driven solutions are feasible, scalable, and meet both technical and business requirements.

What are the key skills and qualifications needed to thrive as a data scientist electrical engineer, and why are they important?

To excel as a Data Scientist Electrical Engineer, you need a solid foundation in electrical engineering principles, statistics, and data analysis, usually supported by a degree in electrical engineering, computer science, or a related field. Proficiency in programming languages like Python or MATLAB, experience with machine learning frameworks, and familiarity with tools such as MATLAB, TensorFlow, and data visualization platforms are typically required. Strong problem-solving skills, effective communication, and the ability to collaborate across multidisciplinary teams are essential soft skills. These skills ensure that professionals can analyze complex engineering data, develop innovative solutions, and communicate insights effectively to drive technical advancements.

What is the difference between Data Scientist Electrical Engineer vs Electrical Engineer?

AspectData Scientist Electrical EngineerElectrical Engineer
Required CredentialsBachelor's or Master's in Electrical Engineering, Data Science, or related fields; certifications like IEEE or data analytics certificationsBachelor's or Master's in Electrical Engineering; Professional Engineer (PE) license often preferred
Work EnvironmentTech companies, R&D labs, industries integrating data analysis with electrical systemsPower plants, manufacturing, construction, and infrastructure projects
Industry UsageData-driven electrical system optimization, predictive maintenance, IoT applicationsDesign, develop, and maintain electrical systems and equipment

Data Scientist Electrical Engineers combine electrical engineering expertise with data analysis skills to optimize electrical systems and develop innovative solutions. In contrast, Electrical Engineers focus on designing and maintaining electrical infrastructure. Both roles require strong technical credentials but differ in their focus on data analytics versus traditional electrical design.

Can an electrical engineer work as a data scientist?

An electrical engineer can work as a data scientist if they acquire relevant skills such as programming in Python or R, understanding of machine learning algorithms, and data analysis techniques. Many data scientists have backgrounds in engineering, mathematics, or computer science, and transitioning often involves additional training or certification in data analytics and statistics.

What are popular job titles related to Data Scientist Electrical Engineer jobs in Florida?

For Data Scientist Electrical Engineer jobs in Florida, the most frequently searched job titles are:

What job categories do people searching Data Scientist Electrical Engineer jobs in Florida look for?

The top searched job categories for Data Scientist Electrical Engineer jobs in Florida are:

What cities in Florida are hiring for Data Scientist Electrical Engineer jobs?

Cities in Florida with the most Data Scientist Electrical Engineer job openings:

Infographic showing various Data Scientist Electrical Engineer job openings in Florida as of August 2026, with employment types broken down into 91% Full Time, and 9% Contract. Highlights an 91% In-person, and 9% Remote job distribution.

Data Scientist

Worldpay, Inc.

Jacksonville, FL • On-site

Full-time

This job post has expired today. Applications are no longer accepted.


Job description

Job Description

Are you curious, motivated, and forward-thinking? At FIS you'll have the opportunity to work on some of the most challenging and relevant issues in financial services and technology. Our talented people empower us, and we believe in being part of a team that is open, collaborative, entrepreneurial, passionate and above all fun.

About the role:

As a key member of the Data Science team, the data scientist will deploy data-driven exploratory analysis as well as predictive models and AI solutions to solve business problems across the financial services industry, particularly in Risk, Fraud, Marketing, and Portfolio Management. Following the machine learning lifecycle, the data scientist should be able to convert the results into actionable product recommendations to present internally and externally.

What you'll be doing:

  • Participate in the design, development, validation, deployment, and monitoring of advanced analytics, machine learning, and AI solutions that drive measurable business outcomes.
  • Leverage expertise in data structures and algorithms to analyze and prepare data for modeling, assembling datasets from both standard and novel data sources and incorporate them into end-to-end analytical solutions.
  • Apply advanced machine learning, predictive analytics, natural language processing (NLP), and emerging AI techniques (GenAI, Agentic etc.) to solve complex business problems across the payments and financial services ecosystem.
  • Design and execute experiments, hypothesis testing frameworks, and statistical analyses to evaluate business strategies, product enhancements, and operational improvements.
  • Establish and promote best practices in data science, machine learning, feature engineering, experimentation, model governance, and MLOps throughout the organization.
  • Stay current on industry trends in machine learning, AI, Generative AI, and financial services analytics; bring relevant innovations to the team.

What you bring:

  • Master's degree or higher in Mathematics, Computer Science, Engineering, Operations Research, Statistics, or a related quantitative discipline.
  • 1-3 years of experience developing and deploying end-to-end machine learning, predictive analytics, and data science solutions within the Payments, Banking, or Financial Services industry.
  • Strong proficiency in Python and SQL; experience with big data technologies such as Spark, PySpark, a plus.
  • Hands-on experience with data wrangling, feature engineering, and model development using libraries such as Pandas, NumPy, Scikit-learn, Matplotlib, Seaborn, or Plotly.
  • Demonstrated experience building and deploying machine learning models in a production or near-production environment.
  • Proficiency with data visualization and business intelligence tools (e.g., Tableau or equivalent).
  • Strong analytical thinking and problem-solving skills; ability to translate ambiguous business problems into rigorous analytical frameworks.
  • Ability to work collaboratively across product, engineering, and business teams.

Nice to have:

  • Experience within the Payments, Banking, or Financial Services industry.
  • Hands-on experience with the Databricks platform, including MLflow, Model Registry, collaborative notebooks, and MLOps workflows.
  • Experience deploying cloud-native machine learning solutions, particularly within AWS environments.
  • Familiarity with emerging advancements in Transformer Models and Agentic AI technologies.
  • Knowledge of model governance, regulatory compliance, and MLOps best practices within regulated financial services environments.

What we offer you:

A career at FIS is more than just a job. It's the chance to shape the future of fintech. At FIS, we offer you:

  • A voice in the future of fintech
  • Always-on learning and development
  • Collaborative work environment
  • Opportunities to give back
  • Competitive salary and benefits


Privacy Statement

FIS is committed to protecting the privacy and security of all personal information that we process in order to provide services to our clients. For specific information on how FIS protects personal information online, please see the Online Privacy Notice.

EEOC Statement

FIS is an equal opportunity employer. We evaluate qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, marital status, genetic information, national origin, disability, veteran status, and other protected characteristics. The EEO is the Law poster is available here supplement document available here


For positions located in the US, the following conditions apply. If you are made a conditional offer of employment, you will be required to undergo a drug test. ADA Disclaimer: In developing this job description care was taken to include all competencies needed to successfully perform in this position. However, for Americans with Disabilities Act (ADA) purposes, the essential functions of the job may or may not have been described for purposes of ADA reasonable accommodation. All reasonable accommodation requests will be reviewed and evaluated on a case-by-case basis.

Sourcing Model

Recruitment at FIS works primarily on a direct sourcing model; a relatively small portion of our hiring is through recruitment agencies. FIS does not accept resumes from recruitment agencies which are not on the preferred supplier list and is not responsible for any related fees for resumes submitted to job postings, our employees, or any other part of our company.

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