Visiting Faculty

8 hours ago

Karve Road Pune Maharashtra, India School of Data Science and Business Intelligence (SDBI) Full time

**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
- 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**:
**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**:
**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

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