Visiting Faculty – Advanced Statistics for Data Science

Visiting Faculty – Advanced Statistics for Data Science

Location: Pune (On-campus Garware College)
Position Type: Visiting / Part-Time
Target Audience: B.Sc. / M.Sc. Data Science Students
Course Duration: 60 Hours (Typically delivered across a semester)

Course Overview:

This course builds foundational and advanced statistical skills for data science students. It covers descriptive and inferential statistics, regression models, multivariate techniques, and practical statistical computing—preparing students to perform real-world data analysis.

Key Topics to Be Taught:

• Descriptive Statistics & Exploratory Data Analysis (EDA)
• Probability Distributions and Sampling Theorems
• Statistical Inference: Estimation & Hypothesis Testing
• Correlation & Regression (Simple, Multiple, Logistic)
• ANOVA, Chi-Square Tests, and Non-Parametric Methods
• Multivariate Statistics: PCA, Factor Analysis, Cluster Analysis
• Introduction to Statistical Computing using Python (or R)
• Hands-on work with real datasets and statistical simulations

Ideal Candidate Profile:

• Postgraduate or PhD in Statistics, Mathematics, Data Science, or a related field
• Strong command of statistical software/tools such as Python (NumPy, pandas, statsmodels, seaborn) or R
• Prior teaching or corporate training experience in applied statistics is preferred
• Ability to engage students through practical assignments, projects, and datasets
• Passionate about applying statistics in real-life contexts (business, research, etc.)

Commitment & Delivery Format:

• ~60 hours per semester
• Weekly 4–6 hours of lectures + hands-on lab sessions
• On-campus, at a Pune-based institute

How to apply:

Send resume to [email protected] or apply directly here

Job Types: Part-time, Contractual / Temporary
Contract length: 4 months

Pay: ₹30,000.00 - ₹50,000.00 per month

Schedule:

• Day shift

Experience:

• Higher education teaching: 5 years (Preferred)
• Statistics: 3 years (Preferred)

Language:

• English (Preferred)

Work Location: In person