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Entry Level Data Science Jobs in Miami, FL (NOW HIRING)

Pwc

Data Engineer - Senior Associate

Miami, FL

$77K - $202K/yr

Management Information Systems, Computer and Information Science, Systems Engineering, Electrical ... PwC does not intend to hire experienced or entry level job seekers who will need, now or in the ...

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Entry Level Data Science information

See Miami, FL salary details

$10

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How much do entry level data science jobs pay per hour?

As of Jul 19, 2026, the average hourly pay for entry level data science in Miami, FL is $18.19, according to ZipRecruiter salary data. Most workers in this role earn between $15.38 and $20.43 per hour, depending on experience, location, and employer.

Is 40 too late for data science?

Entry level data science roles are open to candidates of all ages, including those starting a career at 40 or older. Success depends on acquiring relevant skills such as programming, statistics, and data analysis, often through online courses or certifications, regardless of age.

What are entry level data science jobs?

Entry level data science jobs are positions designed for individuals who are starting their careers in the field of data science, often requiring minimal professional experience. These roles typically involve working with data collection, cleaning, and analysis, as well as assisting more senior data scientists with projects. Entry level data scientists are expected to have a foundational understanding of statistics, programming (often in Python or R), and basic machine learning concepts. They may work in various industries, helping organizations gain insights from data to support decision-making.

How do I become a data scientist with no experience?

To become an entry-level data scientist with no experience, focus on building foundational skills in programming languages like Python or R, and learn data analysis and visualization tools such as SQL and Tableau. Completing online courses, working on personal projects, and participating in competitions like Kaggle can demonstrate your abilities and help you gain practical experience. Earning relevant certifications and creating a strong portfolio can improve your chances of entering the field.

What is the 80 20 rule in data science?

In data science, the 80/20 rule, also known as Pareto principle, suggests that roughly 80% of results come from 20% of the efforts or features. Entry level data scientists often focus on identifying the most impactful variables or tasks to optimize model performance and efficiency.

What types of projects or tasks can I expect to work on as an entry-level data scientist?

As an entry-level data scientist, you'll typically work on tasks such as data cleaning, exploratory data analysis, and supporting the development of predictive models. You may also assist in preparing datasets, generating reports, and visualizing data for stakeholders. Collaboration with more senior data scientists and cross-functional teams like engineering or business analysts is common, giving you opportunities to learn and grow your technical and communication skills. These foundational projects are essential for building your expertise and preparing for more complex responsibilities as you advance in your career.

What are the key skills and qualifications needed to thrive as an Entry Level Data Scientist, and why are they important?

To thrive as an Entry Level Data Scientist, you need a strong background in statistics, programming (often Python or R), and data analysis, typically supported by a relevant degree such as computer science, mathematics, or statistics. Familiarity with technical tools like SQL databases, data visualization software (e.g., Tableau), and machine learning libraries (such as scikit-learn or TensorFlow) is commonly expected. Curiosity, problem-solving ability, and effective communication help you interpret data insights and collaborate with diverse teams. These skills ensure you can extract meaningful insights from data, contribute to data-driven decision-making, and grow within the analytics field.

What is the difference between Entry Level Data Science vs Data Analyst?

AspectEntry Level Data ScienceData Analyst
Required CredentialsBachelor's in CS, Statistics, or related field; some certificationsBachelor's in Business, Statistics, or related field; certifications optional
Work EnvironmentTech companies, startups, research labsBusiness, marketing, finance sectors
Employer & Industry UsageData-driven roles in tech and researchBusiness insights, reporting, and visualization
Common Search & ComparisonYesYes

Entry Level Data Science and Data Analyst roles often share similar educational backgrounds and work environments. However, data scientists typically focus on building models and advanced analytics, while data analysts concentrate on interpreting data and creating reports. Both roles are essential in data-driven organizations, but they differ in technical complexity and scope.

Can I get a data scientist job with no experience?

Entry-level data science positions often require some knowledge of programming languages like Python or R, and familiarity with data analysis tools. While prior experience is not always mandatory, demonstrating relevant skills through projects, certifications, or coursework can improve your chances of securing an entry-level role.
What are the most commonly searched types of Data Science jobs in Miami, FL? The most popular types of Data Science jobs in Miami, FL are:
What are popular job titles related to Entry Level Data Science jobs in Miami, FL? For Entry Level Data Science jobs in Miami, FL, the most frequently searched job titles are:
What job categories do people searching Entry Level Data Science jobs in Miami, FL look for? The top searched job categories for Entry Level Data Science jobs in Miami, FL are:
What cities near Miami, FL are hiring for Entry Level Data Science jobs? Cities near Miami, FL with the most Entry Level Data Science job openings:
Entry Level Data Science jobs near you
Data Scientist

Data Scientist

Zimmerman Advertising

Fort Lauderdale, FL • On-site

Full-time

This job post has expired 2 days ago. Applications are no longer accepted.

Job description

The Data Scientist works closely with Retail Technology, Media and Account Services teams to provide predictive modeling of Marketing, Direct & Digital Efforts. We are looking for a motivated Data Scientist and analytical thought leader. This is a rare opportunity to be part of a diverse and newly expanded analytics department and a great fit for a predictive modeler with a desire to impact business results.

Responsibilities

  • Apply specialized technical knowledge and expertise to perform reviews relating to the full life cycle of models, information technology applications, or risk management/analysis used across the company.
  • Collaborate and share knowledge with teams across the media organization, as appropriate. Build and maintain relationships with business partners at the manager and staff levels.
  • Use data analysis, mining, and migration techniques for enhanced targeting, audience segmentation, clustering, profiling, and regression analysis
  • Identify digital placement-level strengths and weaknesses across simultaneous campaigns and geographies
  • Develop and maintain internal automated reporting tools, documents, scoring systems, and dashboards for on-going and post-campaign reporting
  • Coordinate cross-functional reviews to discuss region- and campaign-specific findings and actionable recommendations for digital media campaigns built on various CPM, CPC, CPE, and CPA models
  • Identify and facilitate resolution of tagging issues in coordination with Traffic and Production teams focused on site-side tracking, reporting, and implementation
  • Provide client-facing/non-technical recommendations and insights, both in a written and verbal manner, that provide understandable and actionable optimizations.
  • Work with Media, Strategic Intelligence and Account Services teams to develop measurement plans to deliver on campaign and client objectives

Requirements

  • Bachelor’s degree in related field
  • Entry-Level and/or College Internship experience 
  • Must demonstrate the ability to successfully develop and run analytics (scripts) using specialized tools and platforms, specifically, R, Python, SQL, and/or SAS.
  • Experience applying data synthesis, mining and regression techniques for enhanced targeting, audience segmentation, clustering, profiling, and insightful recommendations
  • Advanced knowledge of Microsoft Excel
  • General understanding of digital advertising, digital media strategy, ad placement type, placement-level insight, and standard media metrics is preferred
  • Experience with data orchestration tools such as Annalect Omni is preferred
  • Excellent verbal, written and interpersonal communication skills
  • Ability to work independently and as part of a team
  • Ability to manage multiple projects simultaneously while meeting deadlines
  • Regression modeling focusing on maximizing yield while measuring the diminishing returns of ad spend at scale for thousands of locations.
  • Data storytelling and presentation

Required Skills
Required Experience

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