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Senior Python Data Science Jobs in Connecticut (NOW HIRING)

Python Tutor

Hartford, CT · Remote

$18 - $40/hr

... students for data science, web development, automation, and computer science coursework ... Familiar with Python curricula at introductory through advanced levels and common challenges such ...

Python Tutor

Stamford, CT · Remote

$18 - $40/hr

... students for data science, web development, automation, and computer science coursework ... Familiar with Python curricula at introductory through advanced levels and common challenges such ...

Python Tutor

Norwalk, CT · Remote

$18 - $40/hr

... students for data science, web development, automation, and computer science coursework ... Familiar with Python curricula at introductory through advanced levels and common challenges such ...

Python Tutor

Bridgeport, CT · Remote

$18 - $40/hr

... students for data science, web development, automation, and computer science coursework ... Familiar with Python curricula at introductory through advanced levels and common challenges such ...

Python Tutor

New Haven, CT · Remote

$18 - $40/hr

... students for data science, web development, automation, and computer science coursework ... Familiar with Python curricula at introductory through advanced levels and common challenges such ...

In this position, you will work independently on data science projects of any scale and you will be ... Hands-on experience in Python, R, SQL, Scala * Exposure to cloud computing (Azure, AWS, etc.

In this position, you will work independently on data science projects of any scale and you will be ... Hands-on experience in Python, R, SQL, Scala * Exposure to cloud computing (Azure, AWS, etc.

In this position, you will work independently on data science projects of any scale and you will be ... Hands-on experience in Python, R, SQL, Scala * Exposure to cloud computing (Azure, AWS, etc.

Showing results 21-40

Senior Python Data Science information

What is the difference between Senior Python Data Science vs Data Analyst?

AspectSenior Python Data ScienceData Analyst
Required SkillsPython, machine learning, statistical analysis, data modelingExcel, SQL, data visualization, basic statistics
Work EnvironmentData science teams, R&D, product developmentBusiness units, reporting, operational analysis
Industry UsageTech, finance, healthcare, e-commerceRetail, marketing, finance, healthcare

Senior Python Data Scientists focus on advanced analytics, machine learning, and building predictive models using Python, often working in R&D or product teams. Data Analysts primarily handle data reporting, visualization, and basic statistical analysis to support business decisions. While both roles require data handling skills, Senior Python Data Science roles demand deeper technical expertise and experience with complex algorithms.

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Senior Lecturer in Data Science and Artificial Intelligence (AI) in Public Health

Yale University

New Haven, CT • On-site

Full-time

Re-posted 17 days ago


Key responsibilities

  • Develop and deliver courses on AI in Public Health.

  • Help build institutional capacity through workshops, short courses, summer programs, and certificate programs related to data science and AI in public health.

  • Collaborate with colleagues across Yale School of Public Health and Yale to enhance teaching and training at the intersection of AI, data science, and public health.


Yale University rating

8.2

Company rating: 8.2 out of 10

Based on 65 frontline employees who took The Breakroom Quiz

152nd of 631 rated colleges and universities


Job description

Description
The Yale School of Public Health (YSPH), Data Science and Data Equity (DSDE) Initiative invites applications for a Senior Lecturer in Data Science and Artificial Intelligence (AI) in Public Health. This is a teaching - and training - focused faculty appointment for an individual who will help advance DSDE's educational mission by developing and delivering high-quality instruction in data science and artificial intelligence and its responsible application in public health research, practice, and policy. The home department within YSPH will be decided based on background of the applicant.
The successful candidate will contribute to YSPH's growing efforts to prepare students to understand, evaluate, and apply AI methods in ways that are rigorous, ethical, and relevant to real-world public health contexts. The Senior Lecturer will develop and teach courses on AI in Public Health and help build institutional capacity through workshops, short courses, summer programs, certificate programs, and other educational programming and offerings for students, faculty, and staff.
This faculty member will work collaboratively with colleagues across YSPH and Yale to strengthen teaching and training at the intersection of AI, data science, and public health. The ideal candidate will bring strong applied expertise, a record of exceptional teaching and educational leadership, and the ability to connect emerging AI methods and tools with the needs of public health learners and practitioners.
Senior Lecturer Expectations
In keeping with Yale's expectations for Senior Lecturers, the successful candidate will demonstrate:
  • Superior teaching that effectively brings practice into the classroom in a way that is linked to a rigorous body of knowledge.
  • Intensive engagement in the activities of the School, such that the YSPH position is the faculty member's primary career focus.
  • Hands-on coding and visualization expertise in R and Python augmented by new AI capabilities to support an applied researcher/student with cutting-edge use of data science and AI.
  • Through teaching and engagement, the provision of experience and expertise that the School views as essential but otherwise lacks in the area of AI in Public Health.
  • Serve as an academic lead for the launch of certificate programs in data science and AI in public health.

Qualifications
  • A graduate degree in a relevant field such as public health, biostatistics, epidemiology, data science, computer science, informatics, mathematics, health services research, health policy, or a related discipline.
  • Demonstrated expertise in AI methods and their applications in public health or closely related domains.
  • Demonstrated experience with coding in R and Python.
  • Evidence of exceptional teaching ability and educational leadership, such as prior instruction, curriculum development, training leadership, workshop facilitation, or comparable contributions.
  • Demonstrated ability to teach technical concepts clearly to learners with varied backgrounds.
  • Commitment to an academic environment that values intellectual rigor, integrity, and inclusive excellence.

Preferred
  • Doctoral degree in a relevant field.
  • Prior experience teaching graduate students and/or professionals.
  • Experience applying AI in public health practice settings such as government, health systems, nongovernmental organizations, implementation settings, industry, or research environments.
  • Experience teaching or developing content on responsible AI, including topics such as ethics, fairness, transparency, governance, privacy, and evaluation.
  • Experience with generative AI, large language models, or related computational tools, especially in ways that support teaching, training, or applied public health problem-solving.
  • A record of 5 or more years of exceptional teaching and educational leadership consistent with Senior Lecturer consideration.

Application Instructions
Yale University and the Yale School of Public Health are committed to excellence. We welcome applications from candidates who will contribute to the academic vitality of YSPH and to the education of public health leaders prepared to use AI responsibly and effectively for population health impact.
Appointment terms, start date, and compensation are competitive and commensurate with qualifications and experience.
Applicants should submit:
  1. A cover letter describing interest in the position and relevant experience in teaching data science and AI in Public Health.
  2. Curriculum vitae.
  3. A teaching statement that describes the applicant's approach to instruction, inclusive teaching, and integration of applied practice with scholarly rigor.
  4. Sample syllabi or course/workshop materials, if available (including an AI use policy).
  5. Teaching evaluations, if available.
  6. Names and contact information for three references.

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