Learning Outcome Lead

NXTWAVE

Learning Outcome Lead

Academy

Location

Hyderabad (In-Office)

Employment Type

Full-Time

Work Schedule

6 days a week, 9:30 AM – 6:30 PM, with 1st & 3rd Saturday off

Openings

1 (Academy)

About NxtWave

NxtWave is one of Indias fastest-growing ed-tech startups, reshaping the tech education landscape by bridging the gap between industry needs and student readiness. With prestigious recognitions such as Technology Pioneer 2024 by the World Economic Forum and Forbes India 30 Under 30, NxtWaves impact continues to grow rapidly across India.

About the Role

A student can pass every assessment NxtWave designs and still not be ready for the job market — because the assessment stopped reflecting what companies actually test for six months ago. Thats the gap the Learning Outcome Team exists to close: making sure that clearing our bar for competency means something in a real interview, not just on an internal dashboard.

This isnt a content or assessment-design role — you wont be writing test questions or building courseware yourself. Youll be the person who makes sure the people who do — Assessment Design, Content, Learning — are building the right thing, informed by whats actually happening in the Academys hiring pipeline right now. Youll also help shape the learning, content and placement-prep program itself: not just whats taught, but how its sequenced and paced so competency actually compounds into hire-readiness.

Everything this team touches — the assessments, the curriculum, the prep programs — is Software Engineering: SDE, full stack, backend, AI/ML, data. You need to be someone who can read the code being tested, not just read about it.

Hiring bars are moving fast in the AI era, and if the competency framework doesnt move with them, assessment-qualified stops meaning hireable. Youll need to catch that drift early, and use AI yourself to keep pace with it rather than manually re-deriving frameworks every cycle.

Key Responsibilities

• Drive Assessment Success: Improve assessment pass rates and competency mastery across Academy; identify learning bottlenecks and track outcomes across domains.
• Assessment Design Partnership: Bring Academy-specific context and hiring intelligence (interview patterns, coding trends, company evaluation criteria, emerging technologies) to the Assessment Design Team, and work with them to ensure assessments accurately reflect real hiring requirements — you inform and review assessment design, you dont author assessments directly.
• Content & Learning Partnership: Bring Academy context and assessment/competency requirements to the Content and Learning teams, and work with them to ensure learning material and formats actually prepare students for whats being assessed — in partnership, not as the sole content owner.
• Learning & Placement-Prep Program Design: Help design the overall learning and placement-prep program structure (sequencing, milestones, prep formats) for Academy in a way that measurably drives competency progression and hiring outcomes.
• Build Student Competency Signals: Help design and run hackathons, coding contests, projects, and practical evaluations to build a fuller picture of student capability beyond test scores.
• Design Competency Evaluation Strategies: Build multi-stage evaluation frameworks and skill-level classification models that map students to the right opportunity segments (e.g., high-paying SDE roles, AI/ML, full stack, backend, frontend, data roles).
• AI-Driven Process Improvement: Use AI tools to improve evaluation efficiency, competency signal generation, and how inputs are synthesized for the Assessment Design and Content teams — rather than running these processes only manually.
• Team Leadership: Build, manage, and coach a team (competency analysts, evaluators, coordinators) of 8–10 members with clear weekly KPIs tied to learning outcomes, not just activity volume.
• Cross-Functional Collaboration: Work closely with Hiring, Assessment Design, Content, Learning, and Placement Partnership teams to close the loop between hiring outcomes and the learning system.

Key Outcomes

• Assessment Qualification Rate: Improve the percentage of students successfully qualifying assessments across competencies for Academy.
• Competency Progression: Track and improve student movement across skill levels — Beginner → Intermediate → Advanced → Placement Ready [Academy-specific target].
• Placement Readiness: Increase the number of students who become eligible for hiring opportunities based on demonstrated competency.
• Industry Alignment: Keep assessments and content aligned with current hiring trends, in-demand technologies, and emerging skills [Academy-specific target].
• Team Performance: Run a high-performing team of 8–10 with clear weekly KPIs on turnaround of inputs to Assessment Design and Content teams, review cycles, and competency-signal generation.

Non-Negotiables

• 4+ years of overall experience, with proven end-to-end ownership of an assessment, curriculum, or competency-validation function.
• Strong programming and software development background — able to critically evaluate technical assessment content (DSA, coding, projects) and give informed design inputs to the Assessment Design team, since Academys curriculum and assessments are Software Engineering-focused.
• Experience managing or closely leading a team of 5–8 — competency analysts, evaluators, coordinators, or similar.

You Might Be a Good Fit If

• You can spot the difference between an assessment that tests real competency and one that just tests whether someone memorized the syllabus — and you push back when you see the second kind.
• You bring hard hiring-intelligence context into a room full of assessment and content owners and change what they build, without ever writing the assessment yourself.
• You think about a students learning journey as a system with levers — sequencing, milestones, prep formats — not a fixed syllabus you maintain.
• Youre already tracking how AI is changing what companies test for, and rebuilding competency frameworks around that shift before it shows up as a drop in placement readiness.
• You use AI to move faster at your own job — synthesizing hiring intelligence, generating competency signals — not just as a tool you mention in interviews.
• You can hold multiple cross-functional teams (Assessment Design, Content, Learning, Hiring) accountable to a shared outcome without owning their headcount.
• Youre comfortable being judged on whether assessment-qualified actually predicts gets hired — not on how many assessments got shipped.

Strong Candidates May Also Have

• Prior experience in ed-tech, assessment design, or curriculum development.
• Familiarity with technical hiring processes and company-specific evaluation criteria.
• Exposure to competency frameworks, skill-classification models, or learning analytics tools.

What Makes This Role Exciting

• You get to define what ready actually means for thousands of students, at the exact moment AI is redefining what companies hire for.
• You sit at the one point in the org that connects hiring reality to how we teach and evaluate — get it right and every downstream team ships better.