Angel One
Website:
angelone.in
Job details:
About Angel One:
Angel One is one of India’s fastest growing fin-techs, on a bold mission to make investing simple, smart, and inclusive for every Indian. With over 3+ crore clients, we’re building at scale – and building for impact.
Our Super App helps clients manage their investments, trade seamlessly, and access financial tools tailored to their goals. We are working to build personalized financial journeys for our clients, powered by new-age tech, AI, Machine Learning and Data Science.
We're a builder's company at heart. You’ll have the space to experiment, the freedom to move with velocity, and the mandate to make bold, user-first decisions – every single day.
The vibe? Think less hierarchy, more momentum. Everyone has a seat at the table and a shot to build something that lasts.
Be part of a team that’s scaling sustainably, thinking big, and building for the next billion.
Why You'll Love Working at Angel One!
- Tech Systems that run at Scale: From AI to real-time data infra, you’ll work on tech that’s ahead of the curve and solve problems that truly matter.
- Build one of India’s Leading Fintech Platform: We’re not just disrupting finance – we’re shaping how billion Indians access wealth.
- Own It. Drive It. Scale It: You’ll have the freedom to lead, the resources to build, and the opportunity to leave your mark.
- Empowered Growth: We invest in your growth and empower you to explore your full potential.
- Exceptional Benefits: Our comprehensive benefits package includes health insurance, wellness programs, learning & development opportunities, and more.
Job Title: Senior Manager – People Analytics & AI
Location: Bengaluru
The Opportunity
Most organisations collect people data. Very few know what to do with it. We are building the capability to change that — and this role is at the centre of it.
Over the past three years, we have built a data engineering foundation that most People Analytics teams only aspire to — a mature HR Data Mart, reliable pipelines, and an established reporting layer. The groundwork is done. What we are looking for now is someone who can take everything that foundation was built to support and make it real: predictive intelligence that is actually embedded in talent decisions, AI agents that answer leadership questions in real time, and proactive insights that reach every level of the organisation without anyone having to ask.
You will work on problems that genuinely do not have solved answers yet: Can we predict with precision which teams are at flight risk six months from now? Can an AI agent answer a VP's workforce question in real time — in plain English, without a ticket to the analytics team? Can exit interview themes surface automatically and reach leadership the morning after they are collected?
This is not a role for someone who wants to maintain dashboards. It is a role for someone who wants to build the future of how organisations understand their people — on a foundation that is already ready for them.
What You Will Own
1. Data Infrastructure & Intelligence Architecture
You will set the technical direction for how people data flows, transforms, and becomes trustworthy across the organisation. With two internal data engineers and an external infrastructure vendor working under your direction, your leverage is in the quality of decisions you make — on architecture, data modelling standards, pipeline governance, and what gets built and why.
- Define and own the data architecture strategy for the HR Data Mart — determining how data across all HR systems spanning the employee lifecycle is modelled, versioned, and made available for analytics and AI.
- Lead DBT-based transformation workflows — setting standards for modular model design, testing, documentation, and lineage that the engineering team executes against.
- Direct pipeline orchestration on AWS via Apache Airflow — governing reliability, SLA adherence, and data quality across vendor-managed and internal pipelines.
- Own data quality frameworks and validation standards — ensuring every insight produced downstream rests on data that leadership can trust.
2. Decision Intelligence — BI, Reporting & Executive Visibility
We have spent three years building a reporting layer that works. Your mandate now is to scale it — sharper accuracy, deeper adoption, higher sophistication, and broader reach across the organisation. Every dashboard you elevate, every self-serve tool you ship, and every proactive insight you automate is a decision that gets made faster and with more confidence somewhere in the organisation. Your work reaches the C-suite.
- Own and continuously elevate end-to-end People Analytics Tableau dashboards spanning the entire employee lifecycle — raising the bar on accuracy, depth, and executive relevance.
- Build self-serve Streamlit applications that put real-time people metrics directly in the hands of HR Business Partners and business leaders.
- Design and automate proactive intelligence delivery across all leadership levels — ensuring decision-makers receive timely, scheduled workforce insights in the format they consume, without ever having to ask for them.
3. Predictive Intelligence — Data Science & ML
You will move the organisation from describing what happened to knowing what is coming. Your models will be embedded in talent reviews, referenced in leadership conversations, and used to make decisions that affect people's careers.
- Build and own production-grade ML models across people analytics use cases — with attrition and churn prediction as the primary anchor.
- Conduct key driver analysis and hypothesis testing across engagement and survey data to identify the levers that most influence satisfaction, retention, and performance.
- Bring statistical discipline to every people question — and the ability to translate what the data is really saying into decisions a business leader can act on.
4. Frontier Intelligence — Agentic AI & LLM Systems
This is where the role goes beyond anything most People Analytics functions are doing today. You will build AI systems that don't just answer questions — they reason, retrieve, synthesise, and act autonomously on people data.
- Design and deploy multi-step agentic AI workflows using LangChain and LangGraph — systems that can autonomously pull data, cross-reference sources, detect anomalies, and surface insights without human prompting.
- Build a Text-to-SQL agent that allows HR leaders and business partners to query the HR Data Mart in plain English — making the entire people data ecosystem accessible without SQL knowledge.
- Apply LLMs to qualitative data at scale — turning exit interview responses, engagement survey feedback, and eNPS verbatims into structured themes, sentiment signals, and leadership-ready recommendations, automatically.
- Stay at the cutting edge of agentic AI — continuously exploring, prototyping, and bringing emerging agent architectures into production, with one goal: ensuring that every talent decision in the organisation is faster, smarter, and better informed than it was before.
5. Strategic Partnership — Influence Without Authority
The best analytical work is worthless if it doesn't change decisions. You will be the person who makes sure it does.
- Partner with CHRO, HR Business Partners, and business unit leaders to define the questions that matter — and build the analytical products that answer them.
- Shape the People Analytics roadmap — identifying the next frontier of measurement, modelling, and AI adoption, and building the business case to pursue it.
- Govern people metrics and KPI frameworks across the organisation — ensuring consistency, accuracy, and adoption at every level from team lead to board.
Who you are:
- 8+ years in a full-stack analytics, data engineering, or applied data science role — with a track record of shipping analytical products that changed how an organisation made decisions.
- Expert-level SQL across complex queries, window functions, performance tuning, and large-scale relational data warehouses.
- Strong Python proficiency — with the ability to write production-quality analytical and automation code.
- Hands-on experience building and orchestrating ETL pipelines using Apache Airflow on AWS.
- Proven track record designing Tableau dashboards that senior and executive stakeholders actually use to make decisions.
- Experience building and evaluating production-grade ML models — with deep understanding of accuracy, precision, recall, and business interpretability trade-offs.
- Real-world experience with Large Language Models — shipped applications in text analysis, theme extraction, summarisation, or structured insight generation from unstructured data.
- Strong statistical foundations — hypothesis testing, key driver analysis, and the ability to explain significance to a non-technical audience.
- The communication skills to present a model to a data engineer and a business case to a CHRO — and have both conversations land.
What Will Set You Apart
- Hands-on experience building agentic AI systems — multi-step agents with tool use, memory, and autonomous reasoning using LangChain, LangGraph, or equivalent frameworks.
- Experience building or deploying Text-to-SQL systems or natural language interfaces over structured enterprise data.
- Working knowledge of DBT — modular model design, testing, documentation, and data lineage in a warehouse environment.
- Experience directing external vendors or third-party engineering teams — setting technical standards, reviewing outputs, and holding delivery accountable.
- Background in HR or people data domains — attrition modelling, engagement measurement, exit analysis, workforce planning, or HRIS data structures.
- Experience with MLOps — model deployment, monitoring, drift detection, and automated retraining pipelines.
Click on Apply to know more.