Data Science Trainer

Securium Solutions; Sector 10; On-site; INR 900,000 - 1,300,000; Full time

Job summary

Securium Solutions invites an energetic Data Science Trainer to mentor learners and deliver end-to-end learning journeys in Data Analytics, Business Analytics, Core Data Science, and Agentic AI workflows. This role blends theory with hands-on projects to prepare learners for tech careers, in-classroom or online.

The ideal candidate has 3+ years of training or industry experience, a strong background in Python, ML/DL, SQL, and data visualization, and excellent communication skills for engaging

Qualifications

• 3+ years delivering classroom or corporate data science training.
• Bachelor's or Master's in CS, data science, statistics, or related.
• Exceptional communication and ability to simplify complex concepts.

Responsibilities

• Curriculum delivery across Data Analytics, Business Analytics, ML/DL, and Agentic AI.
• Hands-on mentorship with live coding, case studies, and capstone projects.
• Monitor student progress, provide feedback, and help build job-ready portfolios.
• Collaborate with Centre Managers, Academic Leads, and Operations for scheduling and improvements.

Skills

Python

SQL

Excel

ML

DL

NLP

Data Visualization

API Deployment

Education

Bachelor/Master in CS/Data Science

Postgraduate preferred

Tools

Power BI

Tableau

TensorFlow

PyTorch

Scikit-Learn

LangChain

AutoGEN

CrewAI

Job description

Job Title: Data Science Trainer
Location: Classroom (In-Person) / Online
Experience Level: 3+ Years in Training / Industry
Education: B.E. / B.Tech in Computer Science, Data Science, Statistics, or related field (Postgraduate preferred)

About the Role

We are looking for an energetic and experienced Data Science Trainer to mentor and train the next generation of data professionals. In this role, you will lead end-to-end learning journeys covering Data Analytics, Business Analytics, Core Data Science, and cutting-edge Agentic AI workflows. You will blend theoretical foundations with hands‑on, real‑world projects to prepare learners for successful careers in tech.

Key Responsibilities

• Curriculum Delivery: Deliver engaging classroom and online (camera-facing) training sessions across Data Analytics, Business Analytics, Machine Learning, Deep Learning, and Agentic AI.
• Hands‑on Mentorship: Guide learners through live coding sessions, case studies, assignments, and capstone projects using real-world industry datasets.
• Student Progression & Doubt‑Solving: Conduct regular doubt‑clearing sessions, evaluate student performance, provide actionable feedback, and mentor students on building job‑ready portfolios.
• Collaboration: Partner with Centre Managers, Academic Leads, and Operations teams for batch scheduling, learner progress tracking, and program improvements.
• Curriculum & Trend Upgrades: Continuously update course materials, quizzes, and project modules to align with fast‑evolving industry trends (especially modern GenAI and Autonomous AI Frameworks).

Core Skill Domains

1. Data Analytics Skills

• Core Languages & Libraries: Python (NumPy, Pandas, SciPy), SQL for complex data querying, joins, and aggregations.
• Spreadsheet Modeling: Advanced Excel (Pivot tables, VLOOKUP/XLOOKUP, formulas, data validation).
• Exploratory Data Analysis (EDA): Data cleaning, missing value imputation, outlier detection, and statistical summaries.

2. Business Analytics Skills

• Business Intelligence (BI) Tools: Hands‑on expertise in Power BI or Tableau (dashboard design, DAX, data modeling, storyboarding).
• Applied Statistics: Hypothesis testing, AB testing, p-values, ANOVA, regression analysis, and confidence intervals for business decision‑making.
• Problem Frameworks: Translating business problems into data hypotheses, KPI tracking, and domain‑specific case studies (e.g., e‑commerce, finance, healthcare).

3. Data Science & ML/DL Skills

• Machine Learning: Supervised/Unsupervised learning (Linear/Logistic Regression, Decision Trees, Random Forests, XGBoost, Clustering, Recommendation Systems) using Scikit‑Learn.
• Deep Learning & NLP: Neural networks, CNNs, RNNs, and NLP fundamentals using TensorFlow, Keras, or PyTorch.
• Model Deployment Basics: Understanding model evaluation metrics (ROC‑AUC, F1‑Score, RMSE) and basic API deployment.

4. Agentic AI & Next-Gen AI Skills

• Agentic Workflows: Solid understanding of autonomous AI agents, tool calling, memory management, and multi‑agent coordination.
• LLM & Agent Frameworks: Familiarity with modern AI frameworks like LangChain, LangGraph, AutoGEN, or CrewAI.
• Practical AI Applications: Building automated AI pipelines that can plan, execute code, query databases, and generate business insights autonomously.

Requirements & Qualifications

• Experience: Minimum 3+ years of experience delivering classroom, corporate, college, or instructor‑led training sessions in Data Science or Analytics.
• Education: Bachelors or Masters degree in Computer Science, Data Science, Statistics, Mathematics, or a related field.
• Communication: Exceptional verbal, written, and presentation skills with an ability to simplify complex technical concepts.
• Delivery Readiness: Highly comfortable with both in‑person classroom management and camera‑facing online teaching tools (Zoom, MS Teams, LMS platforms).
• Certifications (Preferred): Professional certifications in Data Science, Machine Learning, or Cloud platforms (AWS/Azure Data Analytics) are an added advantage.