About Lifesight
Lifesight is a pioneering Unified Marketing Measurement (UMM) platform which helps marketers measure, plan and optimise their marketing spend. In a world of fragmented data, unreliable cookies, and outdated reporting, we empower modern businesses to achieve predictable, sustained growth by aligning marketing and finance on a single causal truth.
We are at the forefront of Agentic Unified Marketing Measurement. Moving beyond siloed tools and post facto dashboards, our AI-driven causal engine combines Causal MMM, Incrementality testing and Incrementality Adjusted Attribution to create a finance ready marketing decision system.
Why We Exist
Our mission is to eliminate wasted ad spend and remove the guesswork from marketing. Operating as an independent, unbiased measurement layer, Lifesight enables CMOs, CFOs, and performance marketers to confidently answer the only question that matters: What is the true incremental value of my marketing spend?
Join the Future of Decision Intelligence. We are transforming marketing from a gamble into a science. By joining Lifesight, you will help build the intelligent, agent-ready infrastructure that powers data-driven, optimized decisions for hundreds of top global brands.
Position Overview
As the Lead – Technical Implementation on our global Solutions team in Bangalore, you'll lead a team of Technical Implementation Specialists and own data onboarding for Lifesight's Unified Marketing Measurement solutions: Marketing Mix Modeling (MMM), Incrementality Experiments, and Multi-Touch Attribution (MTA).
You'll set the standard for how client data gets into Lifesight: scoped clearly, delivered on time, and accurate from day one. This role is for a hands-on leader who can coach a team, run multiple client onboardings in parallel, and speak with equal confidence to a client's data engineer and their CMO.
What You'll Do
Lead the team
- Lead, mentor, and grow a small team of Technical Implementation Specialists; set priorities, review their work, and raise the bar on quality.
- Allocate client onboardings across the team based on complexity, capacity, and skills; step in hands-on when an engagement needs it.
- Build and maintain standard playbooks, checklists, and templates for data onboarding across MMM, Experiments, and MTA.
- Run regular 1:1s and team reviews; give clear feedback and support each specialist's growth.
Own data onboarding for MMM, Experiments, and MTA
- Own end-to-end data onboarding for every client: scoping data requirements, validating pipelines, testing configurations, and signing off on measurement readiness.
- Define what "model-ready" data looks like for each solution: historical spend, KPI, and control variables for MMM; geo and audience-level data for Experiments; event, touchpoint, and conversion data for MTA.
- Oversee how the team combines, cleans, and transforms fragmented, multi-source data across Excel, SQL, and BigQuery.
- Catch data quality issues early (type mismatches, schema inconsistencies, integration gaps, anomalies, outliers) before they affect client outcomes.
- Troubleshoot and resolve complex implementation issues using internal tooling, APIs, and cross-functional collaboration.
Manage projects and timelines
- Translate client requirements into structured implementation plans with clear milestones, owners, and dates.
- Run multiple onboardings in parallel; track progress, manage dependencies, and keep every project on schedule.
- Spot risks early, escalate with a proposed fix, and keep stakeholders informed.
- Report onboarding status, timelines, and blockers to leadership and client teams.
Be the client's trusted technical partner
- Act as the senior technical point of contact and escalation point for clients during onboarding.
- Lead client calls and workshops; explain data requirements and measurement concepts in plain business language.
- Manage expectations, negotiate scope and timelines, and maintain trust through every engagement.
- Run account health checks and flag risks before they escalate.
Improve how we work
- Use AI tools and prompt engineering to streamline workflows and automate repetitive onboarding tasks across the team.
- Feed structured client and team feedback into Product and Engineering to shape the roadmap and tooling.
- Partner with Data Science, Customer Success, and Sales for smooth handoffs from pre-sales through to model delivery.
P.S. – The above list need not put a ceiling on your aspirations at Lifesight.
What We're Looking For
- 8+ years in technical implementation, data onboarding, solutioning, or solutions consulting within B2B SaaS; ideally in data, martech, or adtech.
- 2+ years leading small teams (3–6 people) of implementation, solutions, or data specialists, including hiring, coaching, and performance feedback.
- Strong client-facing experience: you've owned onboardings end to end and been the go-to technical contact for enterprise clients.
- Excellent business communication: you write clearly, present with confidence, and adapt your message for engineers, marketers, and executives alike.
- Excellent project management: you run several projects at once, plan milestones, manage dependencies, and deliver on time. Experience with tools like Jira, Asana, or similar.
- Proven ability to scope complex client requirements and turn them into structured, actionable implementation plans.
- Hands-on experience combining, cleaning, and transforming fragmented, multi-format data using Excel, SQL, and BigQuery; Python or JavaScript is a plus.
- Sharp data hygiene instincts; you spot type errors, schema mismatches, and structural inconsistencies, and teach your team to do the same.
- Working knowledge of REST APIs, Google Cloud (BigQuery), and SQL-based transformation workflows.
- Active user of AI tools and prompt engineering techniques (Few-Shot Prompting, Role/Persona Prompting, etc.), and keen to drive their adoption across the team.
- First principles thinking. You take ownership, challenge assumptions, and don't let blockers sit, for yourself or your team.
Nice to Have
- Direct experience onboarding data for Marketing Mix Models, Incrementality Experiments (geo or audience holdouts), or Multi-Touch Attribution.
- Familiarity with Tag Managers, JS Pixels / SDKs, server-side tracking, AdTech, DSPs, or marketing attribution tools.
- Familiarity with ad platforms and their data exports and APIs: Google Ads, Meta Ads, Programmatic, and similar ad networks.
- Experience building scalable onboarding processes or internal tooling for a growing implementation team.
- PMP, PRINCE2, Agile, or similar project management certification.