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Phd Python Jobs in Indiana (NOW HIRING)

ClinLab Solutions Group

IN

$61 - $78.25/hr

Develop data visualization and applications in Python, utilizing frameworks such as Streamlit and ... PhD with 7+ years or Master's with 10+ years of industry experience in life sciences, with ...

Jobs for Humanity

Postdoctoral Fellows

Bloomington, IN

$45K - $61K/yr

The ideal individual will have a strong history in coding in R, SASS, and/or Python, Bayesian ... Completed PhD in biostatistics, statistics, computer science, or a related discipline. Strong ...

Lilly

Sr. Scientist - TS/MS Digital Plant

Lebanon, IN · On-site

$87K - $119K/yr

... Python, SIMCA, R) within a cGMP environment. * Collaborate cross-functionally with process ... PhD in Chemistry (Organic, Synthetic, Medicinal, or Analytical) or Engineering; OR B.S. in a ...

Deloitte

AI and Data Science Engineer III

Indianapolis, IN · On-site

$109K - $131K/yr

... Python or R for statistical modeling and data wrangling. * 4+ years of hands-on experience with ... Advanced degree (MS/PhD) and/or relevant certifications (data science and AI/ML). * Experience ...

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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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What job categories do people searching Phd Python jobs in Indiana look for? The top searched job categories for Phd Python jobs in Indiana are:
What cities in Indiana are hiring for Phd Python jobs? Cities in Indiana with the most Phd Python job openings:
Phd Python jobs near you

Scientific Data Architect

ClinLab Solutions Group

IN

$61 - $78.25/hr

Other

Posted 9 days ago

Job description

Job Title: Scientific Data Architect

Work Location: Marion County, Indiana


DOES OFFER RELOCATION



Summary:

Seeking a Scientific Data Architect to drive the design and implementation of advanced scientific data solutions. This role focuses on transforming complex scientific data into actionable insights, collaborating with cross-functional teams, and leveraging AI/ML methodologies to accelerate scientific outcomes. The ideal candidate is a proactive problem-solver with deep experience in life sciences, data modeling, and cloud-based product development.

Responsibilities:

  • Engage directly with scientific stakeholders to understand data challenges and requirements, building strong relationships and accelerating tailored solutions.
  • Design and implement scalable, reusable data models to efficiently organize scientific data for diverse use cases.
  • Translate scientific workflows into robust, cloud-based solutions using advanced data platforms and tools.
  • Prototype and implement solutions including data model design (tabular & JSON), Python-based parser development, and lab software integration via APIs.
  • Develop data visualization and applications in Python, utilizing frameworks such as Streamlit and plotting tools like holoviews and Plotly.
  • Collaborate with business analysts, scientists, and AI engineers to develop and deploy machine learning, AI, mechanistic, statistical, and hybrid models.
  • Iterate dynamically with end users and technical stakeholders, driving solution adoption through regular demos, meetings, and proactive communication.
  • Rapidly learn and apply new technologies to troubleshoot and develop scientific use cases, while contributing to product roadmap prioritization based on user feedback.

Qualifications:

  • PhD with 7+ years or Master’s with 10+ years of industry experience in life sciences, with extensive domain knowledge in drug discovery, preclinical development, CMC, or product quality testing.
  • Proven experience defining, designing, prototyping, and implementing AI/ML-driven use cases in cloud environments.
  • Strong background collaborating with cross-functional teams, including product managers, engineers, and scientific stakeholders.
  • Expertise in exploratory data analysis and workflow optimization to enable novel scientific outcomes.
  • Excellent communication and storytelling skills, with the ability to engage audiences ranging from scientists to executive stakeholders.
  • Consulting experience advising scientists to advance research, development, and quality testing outcomes.
  • Hands-on experience with Python, data modeling (tabular & JSON), API integration, and scientific application development.
  • Demonstrated ability to rapidly learn new tools, technologies, and scientific domains.
  • Strong ownership mentality and a track record of building extensible data models and applications for scientific end users.

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