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Remote Data Scientist Jobs in Altamonte Springs, FL

(unknown company)

Data Scientist

Orlando, FL · On-site +1

Looking for candidate making a career in Data Science with experience applying advanced statistics, data mining and machine learning algorithms to make data-driven predictions using programming ...

IQVIA

Senior Data Team Lead (Remote)

Orlando, FL · Remote

$86K - $217K/yr

This is a remote/WFH position with all necessary equipment provided. What You'll Do * Lead data ... Bachelor's degree in life sciences, health, clinical, biological, or mathematical field. * No less ...

IQVIA

Senior Data Team Lead (Remote)

Orlando, FL · Remote

$86K - $217K/yr

This is a remote/WFH position with all necessary equipment provided. What You'll Do * Lead data ... Bachelor's degree in life sciences, health, clinical, biological, or mathematical field. * No less ...

Worth AI

Data Platform Engineer

Orlando, FL · On-site +1

$106K - $128K/yr

You'll own end-to-end data pipelines and API services that ingest, process, and expose high-quality data to internal customers (data science, analytics, product, and other engineering teams) and ...

SmartIPlace

Business Analyst[remote]

Orlando, FL · Remote

Remote (local to Florida) Visa: USC only Duration: 12 months Education ... Bachelor's degree in Data Science, Information Systems, Business Administration, or related studies ...

4 Corner Resources

Data Engineer

Lake Mary, FL · Remote

$60 - $72/hr

Data Engineer 4 Corner Resources is hiring Data Engineers for a leading healthcare organization ... Remote (Quarterly onsite meetings) * Pay Rate: $60-$72/hr * Duration: 6-month contract-to-hire

4 Corner Resources

Data Engineer

Lake Mary, FL · Remote

$60 - $72/hr

Data Engineer 4 Corner Resources is hiring Data Engineers for a leading healthcare organization ... Remote (Quarterly onsite meetings) * Pay Rate: $60-$72/hr * Duration: 6-month contract-to-hire

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All JobsData Scientist JobsRemote Data Scientist JobsRemote Data Scientist Jobs in Altamonte Springs, FL

Remote Data Scientist information

See Altamonte Springs, FL salary details

$35.1K

$114.7K

$183.7K

How much do remote data scientist jobs pay per year?

As of Sep 5, 2026, the average yearly pay for remote data scientist in Altamonte Springs, FL is $114,731.00, according to ZipRecruiter salary data. Most workers in this role earn between $92,100.00 and $127,100.00 per year, depending on experience, location, and employer.

What is a remote data scientist?

Remote data scientists are professionals who analyze and interpret complex data while working outside of a traditional office environment, typically from home or another remote location. They use statistical methods, machine learning, and programming to extract insights from data, helping organizations make data-driven decisions. Remote data scientists collaborate with teams virtually, often using tools for communication, data analysis, and project management. This flexible work arrangement allows for talent from anywhere to contribute to companies worldwide, provided they have reliable internet and the necessary technical skills.

What does a remote data scientist do?

Remote data scientists collect, confirm, and interpret data to determine useful information for their employer. Unlike in-house data scientists, remote data scientists work outside the office, either from home or another location with Wi-Fi accessibility. Remote data scientists help organizations identify patterns and trends in their data to provide information about lucrative opportunities, necessary improvements, and potential innovations. The information they get from the records they gather helps businesses make decisions in critical areas, such as product development, sales and marketing techniques, and client retention. You find remote data scientists in many different industries, including pharmaceuticals, manufacturing, and banking.

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

To thrive as a Remote Data Scientist, you need strong analytical skills, proficiency in statistics, and a solid background in mathematics or computer science, usually demonstrated through a relevant degree. Familiarity with programming languages like Python or R, experience with machine learning frameworks, and knowledge of data visualization tools are typically required, along with certifications such as Microsoft Certified: Azure Data Scientist Associate or Google Professional Data Engineer. Excellent communication, problem-solving abilities, and self-motivation are critical soft skills for collaborating remotely and delivering insights to stakeholders. These skills are crucial for effectively analyzing data, building predictive models, and driving data-driven decisions in a distributed work environment.

How does a remote data scientist typically collaborate with team members across different time zones?

As a remote data scientist, effective collaboration across time zones often involves leveraging asynchronous communication tools like Slack, project management platforms, and version control systems such as Git. Regular virtual meetings are scheduled to accommodate overlapping hours, and clear documentation becomes crucial for keeping everyone aligned. Proactive communication, sharing progress updates, and setting clear expectations help ensure seamless teamwork despite geographical differences. This structure allows remote data scientists to contribute meaningfully while maintaining flexibility in their work schedules.

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

AspectRemote Data ScientistRemote Data Analyst
Required CredentialsDegree in Data Science, Statistics, or related field; often requires programming skills in Python or RDegree in Analytics, Business, or related field; may require proficiency in Excel, SQL, and visualization tools
Work EnvironmentResearch-focused, developing models, machine learning, and predictive analyticsData interpretation, reporting, and visualization to support business decisions
Employer & Industry UsageTech companies, finance, healthcare, and e-commerceRetail, marketing, finance, and consulting firms

Remote Data Scientists focus on building models and advanced analytics, while Remote Data Analysts interpret data and create reports. Both roles require strong analytical skills but differ in technical depth and project scope.

More about Remote Data Scientist jobs

What are the most commonly searched types of Data Scientist jobs in Altamonte Springs, FL?

The most popular types of Data Scientist jobs in Altamonte Springs, FL are:

What are popular job titles related to Remote Data Scientist jobs in Altamonte Springs, FL?

For Remote Data Scientist jobs in Altamonte Springs, FL, the most frequently searched job titles are:

What cities near Altamonte Springs, FL are hiring for Remote Data Scientist jobs?

Cities near Altamonte Springs, FL with the most Remote Data Scientist job openings:

Remote Data Scientist jobs near you
Infographic showing various Remote Data Scientist job openings in Altamonte Springs, FL as of August 2026, with employment types broken down into 1% As Needed, 80% Full Time, 16% Part Time, and 3% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $114,731 per year, or $55.2 per hour.

Applied Data Scientist

Professional Staffing Services

Orlando, FL • On-site, Remote

Contractor

Re-posted 22 days ago

Job description

Applied Data Scientist - Contract to Hire

Location: Florida (Remote but will need to travel to Orlando for your first day, and for occasional meetings and trainings. )

***Also considering candidates in TX, GA, and NC. Must be willing to travel.

Employment Type: Full-Time, Pay: ~ 140K - 185K

Sponsorship: Not Available (Now or in the future)

About The Company

Our client drives innovative, datadriven insights and scalable AI solutions across the entertainment ecosystem. The Data Science team partners with data engineering, marketing, product, and executive teams to transform audience data into actionable strategies and operational products.

A successful Applied Data Scientist thrives on both analytical creativity and production rigor. As a key member of our client's team, you will own endtoend modeling and deployment work-from the conceptual framing of business problems to data ingestion, model development, and reliable production delivery. Your work will directly shape how our company delivers value to clients and internal stakeholders.

Position Summary & Location Requirements

This is a Florida-based role. While the day-to-day work offers remote flexibility, candidates must reside in the state of Florida or reside in GA, TX, and NC and meet the following travel requirements:

  • Day One: Ability to travel to Orlando, FL or the closest office local to your area for your first day/onboarding.
  • Ongoing: Ability to travel to Orlando or closest office local to your area on occasion for collaborative meetings, trainings, and to support business needs.

Key Responsibilities

In this role, you will bridge the gap between business strategy and technical execution. Specifically, you will:

  • Model & Solution Development: Translate ambiguous business questions into structured analytical and ML solutions. Develop, validate, and optimize models impacting forecasting, segmentation, personalization, recommendation, or operational efficiency.
  • Production & MLOps: Build productionready pipelines and deploy models into scalable environments using robust MLOps practices (CI/CD, automated testing, monitoring), ensuring long-term lifecycle maintenance.
  • Collaboration & Communication: Partner cross-functionally to bridge business requirements and technical design. Communicate insights and technical decisions clearly to both technical and nontechnical stakeholders.
  • Documentation & Standards: Document all models, pipelines, and deployment processes comprehensively to ensure maintainability, reproducibility, and knowledge sharing.
  • Innovation: Stay ahead of emerging tools, techniques, and frameworks in ML/AI to influence best practices across the organization.

Core Qualifications

  • Education: Bachelor's degree in Computer Science, Statistics, Mathematics, or a related quantitative field.
  • Professional Experience: 5+ years of industry experience (excluding internships) in data science and machine learning, including proven ownership of model productization, monitoring, and iterative improvement.
  • Core ML Experience: 3+ years of building machine learning models for business applications (outside of academia), with deep expertise in both supervised and unsupervised learning algorithms.
  • Technical Stack:
  • Python: Strong programming skills with hands-on experience building, training, deploying, and monitoring ML models.
  • SQL: 2+ years of experience with database querying, data preparation, and analysis.
  • Data Warehousing: Working knowledge of large-scale platforms (e.g., Snowflake, SQL Server, BigQuery, Redshift).
  • Cloud Platforms: Familiarity with cloud environments (AWS, Azure, or GCP) and designing end-to-end ML pipelines from ingestion to production serving.
  • Execution Skills: Outstanding analytical skills to diagnose and resolve complex system issues, with a proven ability to manage multiple projects and prioritize tasks effectively.

What Sets You Apart (Preferred Qualifications)

  • Advanced Degree: Master's or Ph.D. in Computer Science, Statistics, Mathematics, or a related quantitative field.
  • Domain Expertise: Industry experience in entertainment or e-commerce, including domains such as theme parks, hospitality, live performances, ticketing, or retail marketplaces.
  • Advanced ML Architectures: Hands-on experience designing and deploying recommendation models (collaborative filtering, content-based, transformer-based) or working with data labeling, taxonomy design, and classification frameworks.
  • Generative AI: Familiarity with GenAI techniques, language modeling, or frameworks like AWS Bedrock and Hugging Face.
  • Deep MLOps Tooling: Advanced experience with tools like SageMaker, Lambda, Airflow, or MLflow, and the ability to guide architectural/strategic decisions for ML infrastructure.

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