Facilitator Data analytics & Data science

Job Description
Job Description
Role: Facilitator – Data Analytics & Data Analysis
Location: Remote (India)
Position Overview
The Facilitator – Data Analytics plays a critical role in delivering high-quality academic support and learning experiences to students enrolled in the Data Analytics program. The Facilitator is responsible for conducting live instructional sessions, supporting students through on-demand tutoring and video explanations, performing quality assurance reviews, and contributing to learner engagement initiatives. This role requires strong analytical expertise, structured problem-solving ability, and the capability to explain complex data concepts clearly to beginner and intermediate learners.

The Facilitator will collaborate closely with mentors and academic teams to improve instructional delivery quality, support newly onboarded experts (MNEs), and contribute to curriculum enhancement aligned with evolving industry expectations. Candidates with strong academic backgrounds and research orientation—particularly PhD holders or candidates currently pursuing a PhD in Data Science, Statistics, Mathematics, Computer Science, or related domains—will be given preference. Eligibility Criteria
Minimum 3+ years of relevant industry and/or teaching experience in Data Analytics or related domains

Strong hands-on experience with modern analytics workflows and business data interpretation

Preference will be given to candidates holding a PhD or pursuing a PhD in Data Science, Statistics, Mathematics, Computer Science, or related disciplines

Bachelor’s or Master’s degree in Data Analytics, Statistics, Mathematics, Computer Science, Engineering, or related domains preferred

Prior experience in EdTech or online instruction is an added advantage

Strong communication skills with the ability to teach US-based learners

Experience conducting sessions using Zoom or similar virtual learning platforms

Strong organizational and time-management skills

Ability to explain complex analytical topics clearly without unnecessary jargon

Strong written and verbal English proficiency

Willingness to work rotational shifts and week-offs based on business requirements

Ability to mentor junior experts and contribute to academic quality improvement initiatives

Primary Responsibilities
Perform all core academic support activities including:
Live Lessons

Weekly Video Tutoring

On-Demand Tutoring Support

QA Review

Maintain a minimum QA score of 80% or above across all assigned activities

Deliver high-quality responses aligned with academic standards during live support interactions

Review mentor session content based on updated internal guidelines

Provide structured feedback on externally sourced academic content across all difficulty levels

Support students through on-demand video explanations

Conduct interactive Q&A sessions to enhance conceptual clarity

Participate in community engagement initiatives to support learner success

Identify learner knowledge gaps and escalate insights to Leads

Train and mentor MNEs during their first 90 days of onboarding

Provide continuous process support to MNEs in their day-to-day academic activities

Collaborate with mentors and academic teams to strengthen delivery quality

Suggest improvements to:
activity guidelines

internal processes

learning workflows

Contribute recommendations for curriculum updates and new course additions aligned with market demand

Monitor incoming academic workload and recommend shift redistribution when required

Prepare contribution reports on:
SME academic effectiveness

live support engagement quality

Curate emerging analytics tools, datasets, and workflows relevant to Data Analytics programs

Secondary Responsibilities
Evaluate video support interactions, live lesson delivery quality, and on-demand tutoring responses as per defined QA standards

Present structured insights and recommendations supporting process improvement initiatives and academic delivery effectiveness

Assist in strengthening instructional delivery frameworks, learner engagement strategies, and overall academic support quality

Support curriculum alignment with evolving data analytics industry expectations and hiring trends

Assist in identifying opportunities to improve learner experience across analytics learning pathways

Subject Expertise Requirements – Data Analytics
Candidates should demonstrate strong working knowledge across the following analytics domains:
Data Analysis Foundations
Data retrieval and querying techniques

Data cleaning and preprocessing workflows

Exploratory data analysis (EDA)

Statistical reasoning and interpretation

Core Tools & Technologies
Industry-level proficiency in:
SQL

Advanced Excel

Tableau

Python

PostgreSQL

Statistical & Experimental Methods
Working knowledge of:
Statistical analysis fundamentals

Experimental design

Hypothesis testing

A/B testing methodologies

Data interpretation for business decision-making

Data Visualization & Communication
Strong ability to:
Communicate business insights from datasets

Create structured dashboards and reports

Build effective visual storytelling using analytics tools

Translate analytical outputs into actionable recommendations

Data Handling & Workflow Skills
Hands-on experience with:
Data extraction workflows

Data cleaning pipelines

Dataset transformation techniques

Structured reporting approaches

Education Requirements
B.Tech / BE / BSc / MSc / M.Tech in Data Analytics, Statistics, Mathematics, Computer Science, Engineering, or related domains

Certifications in Data Analytics / Data Science / Business Analytics preferred

Minimum 15 years of full-time education

Key Competencies
Ideal candidates should demonstrate:
Strong learner empathy

Structured analytical explanation ability

Clear business insight communication skills

Dashboard review and feedback capability

Communication clarity for live instruction

Collaboration with mentors and SMEs

Continuous learning mindset aligned with evolving analytics tools and practices

Strong student advocacy and coaching orientation in fast-paced learning environments

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