Senior Data Analyst

Senior Data Analyst
Client - Product Company
Client is based out of 3 locations - San Francisco, New York, Seattle, or Little Rock
Note - Remote is also ok if you find right candidate, he will have to work in PST time zone
Note - This is a Product company and they build complex Market Analysis platform for very large clients mostly related to Market -Media Domain specialization


About you:

• 12-15+ years of experience in analytics or data science, with expertise in measurement and attribution.
• 3-5 years experience in AdTech industry experience required; familiarity with the TV industry is a plus.
• 3-5+ years of experience in AdTech & Marketing Analytics.
• Skilled in measurement, attribution, funnel analysis, and developing client ready dashboards in SQL, Python, Excel, Tableau, and Sigma
• Hands on exposure to AdTech style analytics through campaign performance, subscription funnel modeling, and event stream data analysis.
• Analyzed campaign performance across Ad Spend, CAC, and impressions to evaluate acquisition efficiency; built Sigma dashboards and delivered recommendations that directly informed campaign scaling and budget allocation decisions.
• Proven track record of creating and presenting data-driven dashboards and presentations, effectively telling a story through insights, with hands-on experience in Metabase, Tableau, and Looker.
• Solid understanding of data modeling techniques, with the ability to explain complex concepts to different audiences.
• Ability to independently prepare analysis using SQL, Python, Excel, and statistical methods.
• Detail-oriented with strong time management skills, delivering high-quality, client-ready analytical reports across multiple projects.
• Comfortable presenting complex analyses to large, non-technical audiences, while also being able to adapt to effectively communicate with technical audiences.

Tech Stack
Programming & Analytics : SQL, Python, Excel, PySpark, Airflow, Snowflake
Business Intelligence & Storytelling : Tableau (Certified), Sigma, Statistical Analysis, A/B Testing, Data Modelling
Certifications: Tableau Certified Analyst (2020), Ongoing: Databricks Academy - Streaming & Lakeflow Declarative Pipelines
Cloud & Big Data: AWS Cloud, Databricks

Most appropriate resume will look like this -

Senior Data Analyst with 9+ years of experience transforming event-level and transactional data into clear, actionable insights across adtech, retail and fintech domains. Skilled in measurement, attribution, funnel analysis, and developing client-ready dashboards in SQL, Python, Excel, Tableau, and Sigma. Strong communicator with experience storytelling to both technical and non-technical audiences. Hands-on exposure to AdTech-style analytics through campaign performance, subscription funnel modeling, and event-stream data analysis.


Tech Stack
Programming & Analytics : SQL, Python, Excel, PySpark, Airflow, Snowflake
Business Intelligence & Storytelling : Tableau (Certified), Sigma, Statistical Analysis, A/B Testing, Data Modelling
Certifications: Tableau Certified Analyst (2020), Ongoing: Databricks Academy - Streaming & Lakeflow Declarative Pipelines
Cloud & Big Data: AWS Cloud, Databricks


AdTech & Marketing Analytics:
Structured multi-platform event data (iOS, Android, Web) into Snowflake models tracking the full user journey - View → Click → Purchase - identifying conversion drop-offs and delivering funnel insights to product and marketing stakeholders.
Analyzed campaign performance across Ad Spend, CAC, and impressions to evaluate acquisition efficiency; built Sigma dashboards and delivered recommendations that directly informed campaign scaling and budget allocation decisions.
Unified fragmented marketing event streams into a consolidated attribution model delivering ~$300K annual cost savings. Built iOS conversion forecasting model and multi-touch attribution logic to estimate ad conversions across partner and campaign levels.
Presented findings, A/B test outcomes to senior business stakeholders and non-technical leadership tailoring storytelling to audience needs.
Fintech & Insurance:
Designed customer identity and analytical models integrating multi-source transactional data (CRM, loyalty, usage signals) in Snowflake to evaluate customer behavior, engagement trends, and retention KPIs - enabling targeted loyalty programs and usage-based insurance analytics at Intact Financial, in close collaboration with business teams to refine metrics and support operational decision-making.


Customer Data Platform & Operational Analytics:
Built a large-scale event-driven data platform using PySpark and Spark SQL to ingest, validate, and transform multi-source client data from SFTP/S3 into curated analytics-ready gold datasets in Snowflake - optimizing Spark jobs for performance and reliability.


Statistical & ML Insights:
Analyzed ML model performance across large experimental datasets in python generating benchmarking reports and visual summaries of model behavior presenting results through HTML-based graphs in client-ready insight reports.

You will:
The Senior Data Analyst will work on reporting and analytics initiatives for client customers. This role will work in close collaboration with Customer Success, Product and Engineering teams. The analyst will be responsible for generating insights from Clean Room technologies, powered by LiveRamp's Clean Room as well as emerging industry solutions such as Amazon Marketing Cloud, Google Ads Data Hub, and more. The role will primarily focus on developing visualizations, dashboards and reports that enable our customers to better understand their data and make data driven decisions.

• Lead measurement initiatives; develop KPIs and learning plans for customers in support of their marketing objectives
• Develop, implement, and maintain analytics systems, tools, and frameworks that enable efficient analysis for customers
• Design approaches for observational analytics - including mining multi-dimensional datasets - and experimental methods to build templates and libraries of analysis that can scale across many different customer use cases and verticals
• Get hands-on with customer data to drive insights, answer key business questions, and enable campaign optimization. Identify and communicate areas to improve effectiveness, efficiency, and productivity.
• Design and create rich, compelling visualizations with data

• Speak and present both internally and externally, leveraging data to tell a story and effectively communicating complex analytical concepts to business and technical audiences.

• Help design new offerings in the analytical space.
• Design and develop insightful dashboards using a variety of data visualization tools to inform decision-making for both internal and external stakeholders.