Job Title: Data Science Trainer Part-Time | Remote

Job Type: Part-Time / Freelance

Work Mode: Remote / Online

Role: Data Science Trainer

Training Audience: Students and working professionals in the USA

Job Description

We are looking for an experienced Data Science Trainer to deliver live, instructor-led online Data Science training to students and working professionals in the USA.

Important: This is a Data Science Trainer role and NOT a full-time Data Scientist position.

The ideal candidate should have strong hands-on Data Science experience and the ability to explain technical concepts through practical demonstrations, hands-on labs, real-world datasets, projects, and industry-oriented scenarios.

Key Responsibilities

- Deliver live online Data Science training to USA-based students and working professionals.
- Strong Statistical and Machine Learning modeling experience
- Advanced programming skills; mastery of a statistical language such as R or SAS; experience using other programming and data manipulation languages (SQL, Hive, Pig, Python, C/C++, Java); familiarity with relational, MPP, and/or Hadoop data management frameworks; proficiency with Microsoft Office tools
- Fluency in at least one deep-learning framework (PyTorch is strongly preferred).
- Train students on Python, NumPy, Pandas, SQL, Statistics, Data Analysis, Data Visualization, and Machine Learning.
- Provide hands-on training on Python programming, Jupyter/Colab, data manipulation, data cleaning, exploratory data analysis, and SQL-based data analysis.
- Train students on Matplotlib, Seaborn, dashboard basics, visualization techniques, and stakeholder-oriented data storytelling.
- Cover probability, distributions, confidence intervals, hypothesis testing, p-values, effect sizes, and A/B testing.
- Train students on Machine Learning fundamentals, feature engineering, preprocessing, train/validation/test splits, cross-validation, model evaluation, and ML pipelines.




- Provide practical training on Regression, Classification, Decision Trees, Random Forests, Boosting concepts, Clustering, K-Means, and PCA.
- Explain machine learning evaluation techniques including MAE, RMSE, precision, recall, ROC-AUC, calibration, error analysis, and model validation.
- Train students on data leakage, class imbalance, feature importance, model interpretation, bias/fairness checks, and reproducible machine learning workflows.
- Provide exposure to Scikit-learn, Git, GitHub, Streamlit, Jupyter Notebook, Google Colab, and other relevant Data Science tools.
- Guide students in developing real-world Data Science projects, dashboards, applications, and GitHub portfolios.
- Conduct hands-on labs, weekly assignments, assessments, project reviews, and technical discussions.
- Mentor students throughout the capstone project, including problem definition, data preparation, EDA, statistical analysis, model development, validation, documentation, and presentation.
- Guide students on presenting their projects and explaining technical decisions during Data Science interviews.
- Adapt teaching methods according to different student skill levels and provide constructive feedback throughout the program.

Required Skills & Experience

- Minimum 5+ years of professional experience in Data Science
- Strong hands-on experience with Python, Pandas, NumPy, SQL, Statistics, Data Visualization, and Machine Learning.
- Strong practical experience with Scikit-learn, Matplotlib, Seaborn, Jupyter Notebook / Google Colab, Git/GitHub,



and related Data Science tools.
- Valuable knowledge of data cleaning, EDA, statistical analysis, hypothesis testing, feature engineering, model development, model evaluation, and machine learning workflows.
- Experience working with Regression, Classification, Decision Trees, Random Forests, Clustering, K-Means, PCA, and related machine learning techniques.
- Strong understanding of train/validation/test splits, cross-validation, data leakage, model evaluation metrics, error analysis, and reproducibility.
- Experience building or mentoring end-to-end Data Science projects using real-world datasets.
- Experience with Streamlit or similar tools for creating simple Data Science applications is preferred.
- Strong communication and presentation skills.
- Ability to explain complex Data Science concepts in an easy-to-understand and practical manner.
- Previous experience in training, mentoring, teaching, bootcamps, corporate training, or technical knowledge transfer is highly preferred.
- Experience handling US-based students, professionals, or clients is preferred.
- Must be comfortable delivering live online sessions aligned with USA time zones.

Preferred Certifications

Microsoft Certified: Azure Data Scientist Associate, Google Professional Machine Learning Engineer, AWS Certified Machine Learning Specialty, IBM Data Science Professional Certificate, or comparable Data Science / Machine Learning certifications are preferred.

Important Note

This is a part-time Data Science Trainer opportunity only. Candidates looking exclusively for a full-time Data Scientist / Data Analyst position should not apply.

Candidates should apply only if they have 5+ years of strong hands-on Data Science experience, practical project/mentoring experience, and are comfortable providing live online training to students and working professionals in the USA.

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