Data Analytics Trainer at Hkbk

**JD & KRA — Data Analytics Trainer**
- (Engineering, MBA, BCA, BBA, B.Sc./BCS cohorts)_

**Role Snapshot**

**Field**

**Details**

**Position Title**

Data Analytics Trainer

**Department**

Upskilling & Industry Collaboration

**Learner Segments**

Engineering, MBA, BCA, BBA, B.Sc./BCS

**Core Stack**

**Excel (Adv/Power Query/Power Pivot)**, **SQL (MySQL)**, **Power BI (DAX/Modeling)**, **Tableau**, **Python (NumPy, Pandas, Matplotlib)**, **Applied Statistics & ML (intro)**, **AI-assisted analytics**

**Primary Objectives**

Build industry-ready analytics capability via project-based learning, continuous assessment, placement alignment, and measurable outcome improvements

**Role Summary**

Own end-to-end delivery of a multi-tool analytics curriculum covering Excel, SQL, Power BI, Tableau, Python, Applied Statistics/ML and AI assistants. Design mini/capstone projects and rigorous assignments, run continuous assessments, track each learner’s progress, and collaborate with the Placement Cell to improve tech-round conversions and overall quality.

**Key Responsibilities (JD)**

**A. Curriculum & Delivery**
- Deliver outcome-oriented modules mapped to programme level (UG/PG/Engineering vs Management depth).
- **Excel (Foundations → Advanced)**: formatting, functions, raw-data handling, **Power Query** cleaning & conditional columns, **data connectors**, **Power Pivot** (cardinality, cross-filter).
- **Advanced Excel III**: Pivot Tables, Charts, Slicers, Measures, **Dashboarding**.
- **MySQL**: syntax, clauses/operators, NULL handling; **joins, CASE, GROUP BY, HAVING**; **subqueries, UNION/INTERSECT/EXCEPT, stored procedures, CTEs, window functions**.
- **Power BI**: connectors; **Power Query** (append/merge, pivot/unpivot), **data modelling**, DAX (measures vs calculated columns, time-intelligence, cumulative/moving average), publishing & basic RLS; **visuals & dashboarding** (cards/KPIs/gauges, matrices, slicers) including “ChatGPT-assisted measures” where appropriate.
- **Tableau**: data connections; chart suite; sorting/grouping/filtering; colours/labels/tooltips; **maps, hierarchies, actions, stories, sharing**.
- **Maths & Applied Statistics**: descriptive stats, probability, hypothesis testing, **A/B testing**.
- **Python**: basics → functions/modules, pickle, **NumPy** (stats on arrays), **Pandas** (clean/merge/concat/join), **Matplotlib** charts; **web scraping** (Requests/BeautifulSoup), table extraction, multi-page scraping, basic **text analysis**.
- **ML (Intro)**: regression, decision trees, random forests/ensembles; clustering, hierarchical clustering, dimensionality reduction, cross-validation, evaluation metrics/ROC.
- **AI for Analytics**: using copilots to generate/debug code, data cleaning, **SQL crafting**, model-selection support, anomaly detection—**with accuracy checks and responsible use**.

**B. Projects, Assignments & Portfolios**
- **Mini projects** per module (e.g., Excel margin bridge; SQL cohort analysis; Power BI executive dashboard; Tableau churn story; Pandas data-cleaning pipeline).
- **Capstones** by domain (retail/fintech/ops/HR/marketing): problem framing → ETL → visuals → insights → recommendations/ROI.
- Mandate **portfolio publishing**: Power BI Service/Tableau Public (or screenshots if private) + GitHub (SQL/Python, READMEs).

**C. Continuous Assessment & Progress Tracking**
- Baseline diagnostic; weekly labs/quizzes; timed SQL/Excel tests; dashboard practicals.
- Transparent **rubrics** (data prep, correctness, visual quality, insightfulness, documentation).
- Maintain **progress dashboards** (attendance, scores, milestones, risk flags) and run **remedial clinics** with targeted plans.

**D. Placement Enablement**
- Map teaching to **company patterns** (Excel/SQL tests, dashboard tasks, case interviews).
- Conduct **mock case interviews** and **storytelling drills**; schedule tool sprints before drives; align with roles (BA/DA/MIS/Operations Analyst).

**E. Content Development & Quality**
- Build and refresh **decks, datasets, solution keys, video snippets, quick reference guides**; maintain multi-difficulty question banks; quarterly updates via feedback loops.

**F. Collaboration & Administration**
- Coordinate timetables/labs (licenses/connectors/data sources); ensure compliance with institutional policies and data privacy.
- Submit **attendance, assessment analytics, and placement-readiness reports** on time.

**G. Compliance & Ethics**
- Promote **ethical data use**, citation of sources, fair means in assessments, and zero-plagiarism (plagiarism checks where available).

**Qualifications & Experience**
- **Education**: B.E/B.Tech/M.E./M.Tech/BSCS/MCA/M.Sc. (CS/IT/Stats) or MBA (Analytics/Operations/Marketing).
- **Experience**: 5-8+ years in analytics roles or corporate/ed-tech training with demonstrable projects and outcomes.
- **Skills**: Advanced Excel, strong SQL, Power BI &/or Tableau, statistics for decisions, Python (desirable), data storytelling; evidenc