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Part Time Data Science Engineer information

What is the difference between Part Time Data Science Engineer vs Data Analyst?

AspectPart Time Data Science EngineerData Analyst
Required CredentialsBachelor's or Master's in Data Science, Computer Science, or related fields; knowledge of programming languages like Python or RBachelor's degree in Statistics, Mathematics, or related fields; proficiency in Excel, SQL, and visualization tools
Work EnvironmentProject-based, flexible hours, often remote or freelanceOffice or remote, regular hours, often in corporate settings
Employer & Industry UsageTech companies, startups, consulting firmsFinance, marketing, healthcare, retail

Part Time Data Science Engineers focus on building models and advanced analytics, often requiring programming skills and machine learning knowledge. Data Analysts primarily interpret data, create reports, and visualize insights. While both roles analyze data, Data Science Engineers handle more complex modeling tasks, whereas Data Analysts focus on data interpretation and presentation.

What are the most commonly searched types of Data Science Engineer jobs in New York? The most popular types of Data Science Engineer jobs in New York are:
What cities in New York are hiring for Part Time Data Science Engineer jobs? Cities in New York with the most Part Time Data Science Engineer job openings:
Part Time Data Science Engineer jobs near you
Adjunct Lecturer, Fundamentals of Data Engineering (On-Campus, Fall '26)

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

Columbia University

New York, NY • On-site

$11K - $13K/mo

Part-time

Re-posted 10 days 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

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