Data Analyst

About hoichoi

hoichoi is India's leading Bengali OTT platform — the digital arm of SVF, Eastern India's No.1 regional media and entertainment company. We serve ~250 million Bengalis worldwide with 650+ films, 185+ originals, and 3,000+ hours of content.

The Role

This is an analytics role for someone who wants to understand what's actually happening — not just report on it. You'll work across product, content, growth, and marketing to turn raw subscriber and behavioural data into decisions. The platform generates rich signals: what people watch, when they leave, what brings them back, what content converts, and what experience breaks them. Your job is to make sense of those signals faster and more clearly than anyone else in the room.

The right person here is fluent in data tooling, sharp on business context, and allergic to analysis that looks thorough but leads nowhere. You'll be expected to own your outputs — not hand off a dashboard and walk away, but stay in the conversation until the insight has become a decision.

What You'll Do

• Own analytics across key business domains — subscriber growth, content performance, retention and churn, funnel conversion, and campaign effectiveness — building the visibility that product, content, and growth teams need to move quickly.
• Design and maintain dashboards and reporting systems that surface the metrics that matter — and actively deprecate the ones that don't — using tools like Looker, Metabase, Tableau, or equivalent.
• Conduct deep-dive analyses on business questions: why is D30 retention declining in a specific cohort, which content genres drive trial-to-paid conversion, what does the browse-to-play funnel look like by device and geography.
• Build and maintain clean, well-documented data models and SQL pipelines that power both ad hoc analysis and recurring reporting — with enough rigour that others can trust and extend them.
• Partner with product and growth teams on experimentation — define metrics, size samples, ensure clean test design, read results correctly, and communicate findings in a way that drives a decision, not a follow-up meeting.
• Work with the content team on title and genre performance analytics — understand what drives watch time, completion rates, social sharing, and subscriber acquisition by content type.
• Use AI tools (ChatGPT, Claude, AI-assisted BI layers, Jupyter AI) to accelerate data exploration, SQL generation, and synthesis of large analytical outputs — with your judgement on accuracy and validity always in the loop.
• Translate analytical findings into clear, structured communication for leadership and cross-functional stakeholders — the output is a decision, not a deck.

Must-Have Qualifications

• 5-6+ years of data analytics experience with ownership of business-facing analysis — not just support work; you've driven insights that changed a decision.
• Strong SQL proficiency: you can write complex queries, build clean data models, and diagnose data quality issues without hand-holding.
• Experience with at least one BI or dashboarding tool (Looker, Metabase, Tableau, Power BI, or similar) and a track record of building dashboards that actually get used.
• Analytical rigour: you understand statistical concepts well enough to design a valid experiment, read a funnel correctly, and avoid the common pitfalls of self-selected cohorts and confounded metrics.
• Clear, structured communication — you can take a complex analytical finding and present it in two sentences to a founder and in two pages to a product team, and you know which is needed when.
• AI-native workflow: you use AI tools to accelerate data work — SQL drafting, pattern synthesis, report generation — with your own verification layer on every output.

Good-to-Have

• Experience in a consumer subscription product — you understand subscriber lifecycle metrics, cohort analysis, and churn modelling from the inside.
• Python or R proficiency for more complex statistical analysis, data wrangling, or automation beyond what SQL handles cleanly.
• Exposure to content analytics in a media or streaming context — understanding of watch time, completion rates, content affinity, and how recommendation systems interact with organic consumption behaviour.
• Familiarity with event tracking tools and data pipelines (Segment, Amplitude, Mixpanel, dbt, Airflow, or similar) — enough to understand where the data comes from and what can go wrong upstream.

Culture & How We Work

At hoichoi, the best idea wins, not the biggest title. We operate in small, cross-functional teams where content, product, growth, and tech sit close together, argue productively, and occasionally steal each other's snacks. It's a lot like a kitchen during a house party: slightly chaotic, everyone's doing three things at once, but somehow the food comes out great.

Ownership here isn't a buzzword; it's the default setting. If something's broken, you don't file a ticket and wait. You're the person who notices the printer is jammed and just fixes it instead of pretending you didn't see it. We ship fast, measure what works, and iterate. Think less 'perfect deck' and more 'let's see if real viewers actually care.'

When big moments arrive, we stretch. But we're equally serious about keeping the pace sustainable, because burnt-out teams build neither great products nor great stories. If that sounds like your kind of chaos, we should talk.