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Internship Applied Scientist Machine Learning Jobs in Florida

As an ML Applied Scientist, you will support tech leadership by designing and deploying machine learning models and systems, collaborating with cross-functional teams to drive innovation and enhance ...

Opendoor is on a mission to enhance homeownership and is seeking an Applied Scientist to innovate in applied machine learning and AI. This role will significantly impact valuation systems and involve ...

They are seeking an Applied Scientist to advance their machine learning and AI capabilities, focusing on improving valuation systems and tackling various ML challenges. Responsibilities : โ€ข Design ...

Applied Scientist- Pricing

Miami, FL ยท On-site

$156K - $335K/yr

About the Role We're looking for an Applied Scientist to work on some of the hardest quantitative ... Experience with machine learning methods broadly, including where deep learning can complement ...

Applied Scientist AI/ML

Miami, FL ยท On-site

$156K - $355K/yr

About the Role We're looking for an Applied Scientist ( ALL LEVELS ) to push the boundaries of applied machine learning and AI at Opendoor. While this role will have a significant impact on our ...

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Internship Applied Scientist Machine Learning information

What types of projects do Internship Applied Scientists in Machine Learning typically work on, and how do they contribute to the team's goals?

Internship Applied Scientists in Machine Learning often collaborate with multidisciplinary teams to tackle real-world problems using data-driven approaches. Typical projects might include developing and fine-tuning machine learning models, conducting experiments to validate hypotheses, or assisting in the deployment of algorithms into production systems. Interns are expected to contribute fresh perspectives, help with data preprocessing, and perform thorough model evaluations. Through these projects, interns gain hands-on experience while directly supporting the team's research and product development objectives.

What is the difference between Internship Applied Scientist Machine Learning vs Internship Data Scientist?

AspectInternship Applied Scientist Machine LearningInternship Data Scientist
Required CredentialsRelevant degrees in Computer Science, Data Science, or related fields; knowledge of ML frameworksDegrees in Statistics, Data Science, or related fields; strong analytical skills
Work EnvironmentResearch and development teams, focus on ML model developmentBusiness teams, focus on data analysis and insights
Employer & Industry UsageTech companies, AI-focused organizationsVarious industries including tech, finance, healthcare
Comparison Search IntentUnderstanding roles in ML research and developmentUnderstanding data analysis and business insights roles

Internship Applied Scientist Machine Learning roles focus on developing and applying machine learning models, often in research settings. In contrast, Internship Data Scientist positions emphasize analyzing data to generate insights for business decisions. Both roles require strong analytical skills and relevant educational backgrounds, but they differ in their primary focus and work environment.

What are the key skills and qualifications needed to thrive as an Internship Applied Scientist in Machine Learning, and why are they important?

To thrive as an Internship Applied Scientist in Machine Learning, you need a solid background in mathematics, statistics, and computer science, often supported by coursework or research experience in machine learning and data analysis. Familiarity with tools such as Python, TensorFlow, PyTorch, and experience working with large datasets are highly valued, along with knowledge of version control systems like Git. Strong problem-solving skills, curiosity, and the ability to communicate complex concepts clearly set top candidates apart. These competencies are crucial for effectively designing, implementing, and presenting machine learning solutions that address real-world challenges.

What does an Internship Applied Scientist in Machine Learning do?

An Internship Applied Scientist in Machine Learning works on real-world projects involving the design, development, and evaluation of machine learning models and algorithms. Their responsibilities typically include data analysis, building predictive models, experimenting with new techniques, and collaborating with engineers and researchers to solve complex problems. Interns gain hands-on experience with tools like Python, TensorFlow, or PyTorch, and contribute to advancing the company's AI capabilities. The role requires a strong foundation in mathematics, statistics, and computer science, as well as the ability to communicate findings to both technical and non-technical stakeholders.
What are the most commonly searched types of Applied Scientist Machine Learning jobs in Florida? The most popular types of Applied Scientist Machine Learning jobs in Florida are:
What are popular job titles related to Internship Applied Scientist Machine Learning jobs in Florida? For Internship Applied Scientist Machine Learning jobs in Florida, the most frequently searched job titles are:
What job categories do people searching Internship Applied Scientist Machine Learning jobs in Florida look for? The top searched job categories for Internship Applied Scientist Machine Learning jobs in Florida are:
What cities in Florida are hiring for Internship Applied Scientist Machine Learning jobs? Cities in Florida with the most Internship Applied Scientist Machine Learning job openings:
Associate Director, Principal Data Scientist - Applied AI & Machine Learning Engineering

Associate Director, Principal Data Scientist - Applied AI & Machine Learning Engineering

DTCC

Tampa, FL โ€ข On-site

$53K - $54K/yr

Other

Medical, Life, Retirement, PTO

Posted 24 days ago


Job description

Are you ready to make an impact at DTCC?
Do you want to work on innovative projects, collaborate with a dynamic and supportive team, and receive investment in your professional development? At DTCC, we are at the forefront of innovation in the financial markets. We're committed to helping our employees grow and succeed. We believe that you have the skills and drive to make a real impact. We foster a thriving internal community and are committed to creating a workplace that looks like the world that we serve.
Pay and Benefits:
  • Competitive compensation, including base pay and annual incentive
  • Comprehensive health and life insurance and well-being benefits
  • Pension
  • Paid Time Off and Personal/Family Care, and other leaves of absence when needed to support your physical, financial, and emotional well-being.
  • DTCC offers a flexible/hybrid model of 3 days onsite and 2 days remote (onsite Tuesdays, Wednesdays and a third day unique to each team or employee).

The impact you will have in this role:
Being a member of the Technology Research and Innovation team, you will help advance DTCC's ability to explore, validate, and productize emerging data science, machine learning, AI, and GenAI capabilities that create measurable value across the organization. This role sits at the intersection of research, applied machine learning, data engineering, and product development, with a strong focus on moving ideas beyond experimentation into scalable, production-ready solutions. The Principal Data Scientist / Machine Learning Engineer will design and deliver practical, production-oriented solutions in a financial services environment where governance, risk, controls, reliability, and business adoption are critical. This is not a purely theoretical research role; the ideal candidate will have demonstrated experience taking data science, machine learning, AI, or GenAI concepts from ideation through prototype, validation, productization, and deployment while partnering closely with product owners, technology teams, business stakeholders, and innovation leaders to rapidly develop solutions, test feasibility, define a path to production, and align technical work to real business outcomes.
Your Primary Responsibilities:
  • Champion Python-Centric Data Engineering: Spearhead the adoption and optimization of Python for data engineering tasks, including data ingestion, transformation, and advanced analytics. Guide team in leveraging Python libraries and frameworks to build scalable, maintainable solutions
  • Architect Data Pipeline Solutions: Strategically design and implement enterprise-grade data pipelines for optimal data processing thru python and Snowflake. Establish standards for data quality, security, and integrity, and ensure seamless integration of disparate data sources and formats
  • Strategic Cross-Functional Collaboration: Partner with technology teams to identify opportunities for leveraging data and analytics. Translate business requirements into technical solutions and ensure that insights are actionable and aligned with organizational objectives
  • Lead Advanced Machine Learning Initiatives: Direct the design, development, and deployment of robust machine learning models using Python, guiding teams in data preprocessing, feature engineering, model optimization, and evaluation. Oversee the application of advanced techniques, including deep learning, regression, classification, and clustering, to solve high-impact business problems
  • Demonstrate accountability by taking ownership of solution ideation, development, and execution, including coordinating efforts with internal and external teams/stakeholders to present the results (reports and presentations) in a clear and concise manner
  • Technical Leadership and Mentorship: Provide guidance and technical leadership to junior engineers, create high-performance and reusable approaches to solve challenging problems, and cultivate a culture of excellence, continuous learning, and innovation
  • Risk Management and Compliance: Integrate risk and control processes into all data engineering activities, proactively monitor for potential issues, and escalate risks as appropriate to ensure compliance with organizational standards

**NOTE: The Primary Responsibilities of this role are not limited to the details above. **
Qualifications:
  • Minimum 8 years of related experience
  • Bachelor's degree (preferred) or equivalent experience

Talents Needed for Success:
  • Extensive experience in data engineering and machine learning model development using Python
  • Proven expertise in architecting data pipelines with Python and Snowflake
  • Strong leadership and mentorship skills, with experience managing and developing technical teams
  • Excellent communication and collaboration abilities
  • Sound understanding of data governance and risk management
  • Experience in Financial industry is preferred
  • Experience in Data Visualization tools is a plus

We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, sex, gender, gender expression, sexual orientation, age, marital status, veteran status, or disability status. We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.
About Us
With over 50 years of experience, DTCC is the premier post-trade market infrastructure for the global financial services industry. From 20 locations around the world, DTCC, through its subsidiaries, automates, centralizes, and standardizes the processing of financial transactions, mitigating risk, increasing transparency, enhancing performance and driving efficiency for thousands of broker/dealers, custodian banks and asset managers. Industry owned and governed, the firm innovates purposefully, simplifying the complexities of clearing, settlement, asset servicing, transaction processing, trade reporting and data services across asset classes, bringing enhanced resilience and soundness to existing financial markets while advancing the digital asset ecosystem. In 2024, DTCC's subsidiaries processed securities transactions valued at U.S. $3.7 quadrillion and its depository subsidiary provided custody and asset servicing for securities issues from over 150 countries and territories valued at U.S. $99 trillion. DTCC's Global Trade Repository service, through locally registered, licensed, or approved trade repositories, processes more than 25 billion messages annually. To learn more, please visit us at or connect with us on LinkedIn , X , YouTube , Facebook and Instagram .
DTCC proudly supports Flexible Work Arrangements favoring openness and gives people freedom to do their jobs well, by encouraging diverse opinions and emphasizing teamwork. When you join our team, you'll have an opportunity to make meaningful contributions at a company that is recognized as a thought leader in both the financial services and technology industries. A DTCC career is more than a good way to earn a living. It's the chance to make a difference at a company that's truly one of a kind.
Learn more about Clearance and Settlement by clicking here .
About the Team
Serves as a dedicated technology resource for advancing DTCC's business opportunities and providing industry thought leadership for leveraging new technology. The goal of this new department is to partner internally with IT, our business and regulatory divisions and externally with clients, regulators, and fintech vendors, to help build new platforms and business models to advance DTCC's mission to support the financial markets.