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Phd Python Jobs in Florida (NOW HIRING)

STR

Embedded Systems Emulation Engineer

Melbourne, FL · On-site

$110K - $151K/yr

... Python and/or C/C++, and integrate them into system-level simulations and software processing chains * Experience working with hardware components and interfaces * Masters or PhD in related field Pay ...

STR

Embedded Systems Emulation Engineer

Melbourne, FL · On-site

$110K - $151K/yr

... Python and/or C/C++, and integrate them into system-level simulations and software processing chains * Experience working with hardware components and interfaces * Masters or PhD in related field Pay ...

Guru Schools

Senior/Lead AI Engineer

Orlando, FL · On-site

Master's or PhD preferred. * 8+ years of professional experience in software engineering, AI/ML, or ... Python (preferred), TypeScript/Node.js for integrations. * Cloud Platforms: Azure AI/ML services ...

ENSCO, Inc.

Machine Learning Engineer

Melbourne, FL

Python, Matlab,) Demonstrated experience with Deep Learning frameworks (e.g. PyTorch, TensorFlow ... Masters or PhD degree in Machine Learning, Data Science, or Mathematics, or equivalent. Experience ...

Lorven Technologies

Data Scientist

Tampa, FL · On-site

Bring deep ML expertise, strong Python engineering skills, and a nuanced understanding of CPG ... Master's or PhD in Statistics, CS, or related field (preferred) Job / Role Description: * Lead end ...

Lorven technologies

Data Scientist

Tampa, FL · On-site

$130K - $140K/yr

Bring deep ML expertise, strong Python engineering skills, and a nuanced understanding of CPG ... Master's or PhD in Statistics, CS, or related field (preferred) Job / Role Description: * Lead end ...

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Phd Python information

What high paying jobs can I get with a PhD?

A PhD in Python can lead to high-paying roles such as data scientist, machine learning engineer, AI researcher, or quantitative analyst, often requiring advanced programming, statistical skills, and experience with tools like TensorFlow or PyTorch. These positions typically offer salaries above industry average, especially in technology, finance, and research sectors.

Can I do PhD in Python?

A PhD in Python typically refers to research involving the Python programming language, often in computer science or data science fields. While there is no formal PhD in Python itself, students can pursue doctoral degrees in related areas such as computer science, machine learning, or artificial intelligence, where Python is commonly used as a tool for research and development. These programs usually require a strong background in programming, research skills, and knowledge of relevant concepts like algorithms and data analysis.

What are the key skills and qualifications needed to thrive as a PhD-level Python Developer, and why are they important?

To thrive as a PhD-level Python Developer, you need advanced programming skills in Python, a relevant doctoral degree (typically in computer science, data science, or a related field), and a strong foundation in research methodologies. Experience with scientific computing libraries (such as NumPy, pandas, and SciPy), machine learning frameworks, and version control systems like Git is highly valued. Exceptional problem-solving abilities, clear communication, and the capacity to work independently are crucial soft skills for this role. These skills and qualities are essential for driving innovative research, developing robust code, and effectively collaborating within interdisciplinary teams.

Are Python coders still in demand?

Python developers are currently in high demand across various industries due to its versatility in data analysis, machine learning, web development, and automation. Skills in frameworks like Django or Flask, along with proficiency in libraries such as Pandas or TensorFlow, enhance employability in this field.

What types of collaborative projects might a PhD with Python expertise typically engage in within a research or industry setting?

PhDs with strong Python skills often work on multidisciplinary projects that require data analysis, machine learning, or automation. They may collaborate with domain experts, data scientists, and software engineers to design experiments, develop analytical tools, or build scalable research prototypes. Collaborative work frequently involves contributing to codebases, sharing insights through data visualization, and participating in regular meetings to align project goals. Such environments foster both technical growth and exposure to diverse fields, supporting career advancement through impactful contributions.

What is the highest paying job in Python?

The highest paying jobs involving Python typically include roles such as Machine Learning Engineer, Data Scientist, and Quantitative Analyst, especially in finance and technology sectors. These positions often require advanced skills in algorithms, data analysis, and experience with frameworks like TensorFlow or PyTorch, and they can offer salaries exceeding $150,000 annually depending on experience and location.

What is a PhD Python developer?

A PhD Python developer is a professional who has earned a Doctor of Philosophy (PhD) degree and specializes in using the Python programming language for research, data analysis, software development, or academic projects. These individuals often work in fields like data science, machine learning, scientific computing, or academia, where complex problem-solving and advanced analytical skills are required. Their expertise in both research methodologies and Python allows them to tackle sophisticated computational tasks and contribute to cutting-edge innovation.
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Phd Python jobs near you

Senior Data Science Lead - R01566414

Brillio

Tampa, FL • On-site

Full-time

Posted 8 days ago

Job description

About Brillio:
Brillio is one of the fastest growing digital technology service providers and a partner of choice for many Fortune 1000 companies seeking to turn disruption into a competitive advantage through innovative digital adoption. Brillio, renowned for its world-class professionals, referred to as "Brillians", distinguishes itself through their capacity to seamlessly integrate cutting-edge digital and design thinking skills with an unwavering dedication to client satisfaction.
Brillio takes pride in its status as an employer of choice, consistently attracting the most exceptional and talented individuals due to its unwavering emphasis on contemporary, groundbreaking technologies, and exclusive digital projects. Brillio's relentless commitment to providing an exceptional experience to its Brillians and nurturing their full potential consistently garners them the Great Place to Work® certification year after year.
Senior Data Science Lead
Primary Skills
  • Hypothesis Testing, T-Test, Z-Test, Regression (Linear, Logistic), Python/PySpark, SAS/SPSS, Statistical analysis and computing, Probabilistic Graph Models, Great Expectation, Evidently AI, Forecasting (Exponential Smoothing, ARIMA, ARIMAX), Tools(KubeFlow, BentoML), Classification (Decision Trees, SVM), ML Frameworks (TensorFlow, PyTorch, Sci-Kit Learn, CNTK, Keras, MXNet), Distance (Hamming Distance, Euclidean Distance, Manhattan Distance), R/ R Studio

Specialization
  • Data Science Advanced: Data Specialist

Job requirements
  • Experience Range: 12+ years of experience in data science, including hands-on expertise in advanced statistical modeling and machine learning
  • Location: Deerfield Beach, FL
  • Work Type: Hybrid min 3 days onsite per week
  • Key Responsibilities:
    1. Lead the design and implementation of complex data science solutions to drive business impact and inform strategic decision-making
    2. Develop, validate, and optimize advanced statistical and machine learning models, including regression, classification, and forecasting algorithms
    3. Collaborate with cross-functional teams to translate business objectives into actionable analytics projects and deliver measurable outcomes
    4. Mentor and guide junior data scientists, fostering a culture of technical excellence and continuous learning
    5. Leverage Python, R, and relevant frameworks to build scalable data pipelines and automate model deployment using tools such as KubeFlow and BentoML
    6. Conduct rigorous statistical analysis, including hypothesis testing, T-Test, Z-Test, and probabilistic graph modeling to uncover actionable insights
    7. Implement and monitor model validation, explainability, and performance tracking using tools like Great Expectation and Evidently AI
    8. Stay current with emerging trends in machine learning, artificial intelligence, and big data technologies to drive innovation within the team
    Required Skills:
    1. Expertise in hypothesis testing, T-Test, and Z-Test
    2. Advanced proficiency in regression techniques (linear and logistic)
    3. Strong programming skills in Python and PySpark
    4. Experience with SAS or SPSS for statistical analysis and computing
    5. Hands-on knowledge of probabilistic graph models
    6. Proficiency with machine learning frameworks such as TensorFlow, PyTorch, Sci-Kit Learn, CNTK, Keras, or MXNet
    7. Forecasting techniques, including exponential smoothing, ARIMA, and ARIMAX
    8. Experience with model deployment tools such as KubeFlow and BentoML
    9. Strong understanding of classification algorithms (decision trees, SVM)
    10. Proficiency in R and R Studio
    Preferred Skills:
    1. Experience with Great Expectation and Evidently AI for model validation and monitoring
    2. Knowledge of advanced distance metrics (Hamming, Euclidean, Manhattan)
    3. Expertise in scalable data engineering for machine learning pipelines
    4. Hands-on experience with cloud-based machine learning platforms
    5. Familiarity with MLOps best practices and CI/CD for data science
    Desired Qualifications:
    1. Master's or PhD in Data Science, Statistics, Computer Science, Mathematics, or a related quantitative field
    2. Relevant certifications in machine learning, data science, or analytics (e.g., TensorFlow, SAS, or equivalent)

$140 - $150 a year
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We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

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