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Lecturer In Statistics Jobs in New York (NOW HIRING)

... in compensation, statistics, data analytics would be helpful. 3. Applicants with flexibility to teach both daytime and evening classes will receive preference. Preferred Qualifications Equipment ...

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Lecturer In Statistics information

What are the key skills and qualifications needed to thrive as a lecturer in statistics, and why are they important?

To thrive as a Lecturer in Statistics, you need an advanced degree in statistics or a related field, strong analytical skills, and a solid grounding in statistical theory and methods. Familiarity with statistical software such as R, SAS, or SPSS, as well as experience with learning management systems, is typically required. Excellent communication, presentation, and mentoring skills help engage students and facilitate effective learning. These competencies are crucial for delivering high-quality education, supporting student success, and advancing research within the academic environment.

What are some typical challenges faced by a lecturer in statistics when balancing teaching and research responsibilities?

Lecturers in Statistics often juggle the demands of preparing and delivering high-quality lectures with maintaining an active research profile. Managing large class sizes, keeping course content up-to-date with evolving statistical methods, and providing individualized student support can be time-consuming. At the same time, there may be expectations to publish research and contribute to departmental projects, requiring strong time management and prioritization skills. Collaborating with colleagues, seeking research partnerships, and utilizing university support services are common strategies to successfully balance these responsibilities.

What is the difference between Lecturer In Statistics vs Teaching Assistant In Statistics?

AspectLecturer In StatisticsTeaching Assistant In Statistics
Required CredentialsMaster's or PhD in Statistics or related fieldEnrolled in or recent graduate of relevant program
Work EnvironmentUniversity classrooms, lecture halls, research settingsAssisting in courses, grading, tutoring
Employer & Industry UsageHigher education institutions, universitiesUniversities, colleges, academic departments
Common Search & Comparison IntentUnderstanding academic roles, career pathAssisting in courses, entry-level academic support

In summary, a Lecturer In Statistics typically holds advanced degrees and delivers lectures at universities, focusing on teaching and research. A Teaching Assistant In Statistics usually supports faculty by grading, tutoring, and assisting in classes, often being a graduate student. Both roles are integral to academic institutions but differ in responsibilities and qualifications.

What does a lecturer in statistics do?

A Lecturer in Statistics is an academic professional who teaches undergraduate and/or postgraduate courses in statistics at a college or university. Their responsibilities include preparing and delivering lectures, developing course materials, assessing student performance, and providing academic guidance. Additionally, they may conduct research in statistical theory or applied statistics and contribute to departmental administration. Lecturers often stay updated with advances in the field and may participate in academic conferences or publish scholarly papers.
What are popular job titles related to Lecturer In Statistics jobs in New York? For Lecturer In Statistics jobs in New York, the most frequently searched job titles are:
What cities in New York are hiring for Lecturer In Statistics jobs? Cities in New York with the most Lecturer In Statistics job openings:
Infographic showing various Lecturer In Statistics job openings in New York as of August 2026, with employment types broken down into 78% Full Time, 19% Part Time, 1% Temporary, and 2% Contract. Highlights an 85% Physical, 3% Hybrid, and 12% Remote job distribution.

Adjunct Lecturer, Fundamentals of Data Engineering (On-Campus, Fall '26)

Columbia University

New York, NY โ€ข On-site

$11K - $13K/mo

Part-time

Re-posted 19 hours ago


Job description

Company Description
Columbia University has been a leader in higher education in the nation and around the world for more than 250 years. At the core of our wide range of academic inquiry is the commitment to attract and engage the best minds in pursuit of greater human understanding, pioneering new discoveries, and service to society.
The School of Professional Studies at Columbia University offers innovative and rigorous programs that integrate knowledge across disciplinary boundaries, combine theory with practice, leverage the expertise of our students and faculty, and connect global constituencies. Through twenty professional master's degrees, courses for advancement and graduate school preparation, certificate programs, summer courses, high school programs, and a program for learning English as a second language, the School of Professional Studies transforms knowledge and understanding in service of the greater good.
Job Description
Columbia University's Master's in Applied Analytics program seeks experienced industry professionals to serve as a part-time Lecturer for a graduate-level course in Managing Data.
The Fundamentals of Data Engineering course provides students with a foundational context for managing data so that it can be leveraged and used with confidence. Analytic teams work closely with technology partners in managing data. Languages and techniques unique to each team can impede cooperation. To bridge this gap, this course provides a broad overview of data technology concepts including database engines and associated technologies and exposes students to foundational data principles, governance processes, and organizational prerequisites needed to overcome challenges to ensure data quality.
Responsibilities
  • Lead class lectures, instructional activities, and classroom discussion. Attend all class sessions.
  • Monitor and address student concerns and inquiries.
  • Evaluate, grade student work and assessments.
  • Conduct office hours.

Qualifications
Columbia University SPS operates under a scholar-practitioner faculty model, which enables students to learn from faculty possessing outstanding academic training as well as a record of accomplishment as practitioners in an applied industry setting.
Requirements
  • Doctoral degree or equivalent required, in an area related to data science, statistics, computer science, or another discipline that provided rigorous training in quantitative analytics.
  • Knowledge of databases, topics in Big Data, and Data Analysis.
  • Knowledge of SQL and NoSQL databases.
  • Knowledge of Python and Spark.
  • 10+ years of related applied professional experience.

Preferred Skills & Experience
  • Knowledge of MapReduce strongly desired.
  • Other software or programming languages like R and Tableau.
  • Statistical and Machine learning knowledge.
  • University teaching experience.

Additional Information
Salary range: $11,000 - $13,000 per semester long course
Please submit a resume inclusive of university teaching experience.
All your information will be kept confidential according to EEO guidelines.
Columbia University is an Equal Opportunity Employer / Disability / Veteran