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Digital Analytics Data Jobs

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Today

Marketing Data Analyst

Hoover Institution, Stanford University Stanford, CA

Stanford, CA

Today

$41 - $45/hr Full time Marketing Bigquery Business Analytics

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Job Description

Stanford’s Hoover Institution is seeking an Audience & Marketing Insights Analyst to build the analytics foundation behind smarter marketing decisions. In this role, you will design marketing data pipelines and models, then use the data to answer questions about reach, resonance, relationships, and what should change next. Success is measured by the quality of decisions your insights enable.

What you’ll do

Build and maintain automated ELT pipelines that move data from HubSpot, GA4, social, video, podcast, paid media, and event platforms into BigQuery using APIs and native integrations, reducing manual exports.
Organize marketing and audience data in BigQuery using a medallion architecture, and use Dataform transformations to convert raw and semi-structured inputs (including GA4 event export and JSON API responses) into cleaned, reporting-ready tables.
Create and maintain a data dictionary documenting data models, shared identifiers, transformation rules, and metric definitions so marketing, audience, CRM, web, and content data connect reliably.
Monitor pipeline health and data freshness, ensuring failures are caught before they impact reporting, and manage code with Git and GitHub for reproducibility and collaboration.
Handle audience and contact data, credentials, and access responsibly and in line with Stanford privacy and information security policies and applicable regulations.
Ensure campaigns launch with proper tracking, tagging, and measurement plans, including consistent campaign naming and UTM conventions.
Define GA4 event and data layer specifications in partnership with web developers, then QA tracking using tools such as Google Tag Manager preview mode and GA4 DebugView.
Troubleshoot tracking and data-quality issues with Hoover’s web team and external partners, and investigate discrepancies between GA4, HubSpot, and platform-reported figures.
Characterize audience reach using CRM, web, platform, event, and survey data, including geography, profession, content interests, and relationship with Hoover.
Develop measurement frameworks for reach, resonance, and relationships, separating high-volume activity from engaged reading, viewing, and listening.
Analyze cross-channel journeys from social media, search, paid media, video, podcasts, and earned exposure into Hoover-owned channels (Hoover.org, email, and events).
Build audience cohorts and segments based on acquisition source, interests, behavior, and relationship stage.
Evaluate campaigns through pre-, during-, and post-campaign analyses aligned to defined objectives, and identify what content, topics, fellows, formats, and campaigns drive acquisition and repeat engagement.
Measure incremental impact of paid promotion using holdout groups, geographic tests, or platform lift studies where feasible, and distinguish paid, organic, earned, and direct activity.
Analyze marketing costs and outcomes (for example, cost per engaged visitor, new subscriber, and event registrant) to support evidence-based budget allocation.
Partner with marketing leadership to set objectives and measurement plans before major initiatives launch, and design A/B and multivariate tests across email, web, landing pages, paid media, messaging, and creative.
Translate analysis into clear, actionable recommendations that influence decisions about content prioritization, distribution, audience acquisition, and investment.
Build automated cross-channel dashboards (for example, Looker Studio on BigQuery reporting-ready tables) to support self-service visibility for content producers and program teams.
Provide regular reporting and executive-level analysis highlighting metrics plus key findings, implications, and recommended actions for nontechnical audiences.
Proactively identify patterns, opportunities, and risks in the data, and follow up to assess whether changes improved outcomes.

Requirements

Bachelor’s degree in a relevant field and 2 years of relevant experience, or a combination of education and relevant experience solving analytical problems using quantitative approaches.
Experience in marketing analytics, audience analytics, or digital analytics, working directly with marketing, communications, or content teams.
Demonstrated experience combining data from multiple platforms and using it to shape marketing, content, or audience decisions.
Ability to communicate analytical findings to nontechnical stakeholders.

Technical and analytics skills

GA4 (advanced): event-based data model, custom events/parameters/dimensions, key events, Explorations, and correct interpretation of reporting impacts from attribution settings, consent mode, and data thresholding.
Data layer & Tag Management: Google Tag Manager, writing tracking specifications, and debugging implementations.
HubSpot: pulling and analyzing contacts, custom objects, properties, lifecycle stages, lists, marketing email, forms, and subscriptions, including awareness of limitations such as Apple Mail Privacy Protection effects on open rates.
Campaign tracking: UTM tracking, campaign taxonomy, Google Search Console, and native platform analytics (YouTube Studio, Meta Business Suite, LinkedIn, Google Ads) with understanding of metric definitions like views, reach, and engagement.
BigQuery & Dataform: storing, querying, and transforming data (including nested/repeated fields), Dataform workflows with dependencies and data-quality assertions, and cost-aware querying.
SQL: joins, window functions, common table expressions, plus JSON, regular-expression, and text functions.
Python and JavaScript: data processing, automation, API calls, cleaning, statistical analysis, and GTM-related scripting (including Google Apps Script or Dataform as applicable).
ELT and APIs: REST API data retrieval (authentication, pagination, rate limits) and building ELT workflows on Google Cloud with scheduling, monitoring, and error handling.
Data architecture: medallion architecture (bronze/silver/gold), shared identifiers across systems (CRM record IDs, GA4 user IDs, UTM parameters), and consistent metric definitions.
Version control and tooling: Git/GitHub, Visual Studio Code, and command-line tools (Bash, gcloud, bq).
Experimentation: A/B testing, appropriate statistical tests (two-proportion z-tests, t-tests, chi-square tests), power analysis, sample-size calculation, confidence intervals, and avoiding pitfalls like early stopping and multiple comparisons.
Dashboards and reporting: decision-oriented dashboards in Looker Studio and/or Tableau or Power BI, plus strong Google Sheets and Excel for analysis and stakeholder-ready outputs.

Location and schedule

Stanford, CA (onsite).

Compensation: USD 41–45 per hour.

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10d ago

Business Data Scientist, Google Analytics

Google Mountain View, CA

Mountain View, CA

10d ago

$138k - $197k/yr Full time Manager Analytics Business Analytics

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Job Description

This role focuses on applying data science to Google Analytics and media effectiveness measurement, translating analysis into executive-ready strategy, forecasting, and recommendations that influence product adoption and business impact across Ads and Commerce finance.

Role Focus

You will support analytics, insights, and measurement impact across primary web analytics and campaign management platforms. The position supports the media effectiveness measurement team by helping advertisers measure the effectiveness of their digital ad spend using a full-funnel set of metrics.

In addition, you will lead the holistic finance strategy for the GA and CM product suites, partnering with Product Management, Engineering, Product Strategy, Go-To-Market, and cross-functional Finance teams to guide executive decisions.

Key Responsibilities

Shape and scrutinize the commercial strategy for the GA and CM product suites, evaluating impact on business and the broader Google Ads ecosystem.
Drive the annual business plan and define operational goals, delivering executive-level business performance updates and actionable insights.
Architect market sizing and opportunity models to forecast medium-to-long-term product adoption and growth trajectories.
Use cross-functional thinking to assess incrementality and benefits of the product suites within the larger Google user ecosystem.
Serve as a thought partner on incentive fund investments, supporting disbursement operations and flagging risks tied to fund deployment.

About the Team

Google’s leadership team selects complex business challenges, and BizOps works in small teams to find solutions. You will immerse yourself in data collection, derive insight through analysis, and then synthesize recommendations for stakeholders.

You will communicate recommendations to senior executives, support implementation efforts, and revisit outcomes to evaluate the impact of your guidance.

Required Qualifications

Master’s degree in a quantitative discipline such as Statistics, Engineering, Sciences, or equivalent practical experience.
3 years of experience applying analytics to solve product or business problems, including coding (Python, R, SQL), querying databases, performing statistical analysis, or having a relevant PhD degree.

Preferred Qualifications

4 years of experience applying analytics to solve product or business problems, including coding (Python, R, SQL), querying databases, performing statistical analysis, or having a relevant PhD degree.

Technology

Python
R
SQL

Location and Salary

Location: Mountain View, CA (onsite)

Compensation: USD 138,000 - 197,000 per year

Bonus and additional compensation: US: $138000 - $197000 (USD) + 15% bonus target + equity + benefits

Note on pay: Individual pay is determined by job-related skills, experience, and relevant education or training.

Learn more about benefits at Google.

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10d ago

Digital Data Engineer & Analytics Lead

Evereve Incorporated Edina, MN

Edina, MN

10d ago

$85k - $135k/yr Full time Manager Analytics Business Analytics

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Job Description

Own the digital data foundation and BI analytics framework that powers trusted performance measurement across Evereve’s Digital organization.

Responsibilities

Design, build, and maintain scalable digital performance based data pipelines, ETL/ELT processes, governed datasets, and semantic models across digital, marketing, finance, merchandising, technology, and operations sources.
Convert business needs into production-ready reporting assets and reliable data models with clear documentation, monitoring, and quality standards.
Automate manual reporting, expand self-service access, and improve data architecture, lineage, and change management practices.
Define and govern Digital KPIs, including revenue, conversion, AOV, traffic, engagement, funnel performance, delivery speed, shipping margin, returns, and profitability.
Build executive dashboards and reporting frameworks that combine insights from multiple internal and external sources into a single trusted source of truth for Digital performance.
Develop analytical frameworks and financial models supporting business transformation, five-year planning, and technology prioritization.
Support experimentation, A/B testing, digital funnel analysis, and AI-enabled analytics to improve performance forecasting, optimization, and insights.
Turn data into clear insights, recommendations, and business narratives connecting customer behavior, operational performance, and financial outcomes for profitable digital growth opportunities.
Act as the Digital team subject matter expert for data standards, metric definitions, reporting governance, and analytics best practices.
Partner cross-functionally to strengthen reporting discipline, data quality, and adoption of trusted BI tools supporting the Digital business.
Communicate complex technical and analytical topics clearly to senior leaders, peers, and non-technical stakeholders.

Requirements

Bachelor’s degree in Computer Science, Data Engineering, Information Systems, Statistics, Mathematics, Business Analytics, or related field; equivalent experience considered.
Progressive experience in data engineering, BI, analytics engineering, or digital analytics, preferably in retail, ecommerce, omnichannel, or consumer-facing environments.
Hands-on experience with SQL, Power BI, data modeling, ETL/ELT, data warehousing, and dashboard development; Python and SSRS preferred.
Experience with complex, multi-source datasets and building governed reporting, KPI frameworks, and actionable insights.
Strong financial acumen, analytical problem-solving, stakeholder management, communication, and data storytelling skills.

Key Technologies

SQL
Power BI
Python
SSRS
ETL/ELT
Data modeling
Data warehousing

Compensation

USD 85,000 - 135,000 per year

Benefits

Self-Managed PTO: plan and use time off as needed
Affordable Health Insurance: 80% employer-paid premiums for medical and dental; 50% covered for eligible partners, spouses, and dependents
Parental Leave: generous paid leave benefits for maternity, paternity, and adoption
Flex Spending Accounts: pre-tax savings for out-of-pocket healthcare or dependent/daycare costs
Additional Insurance: company paid life insurance and short-term disability
401k +5% Match: 5% company match with immediate vesting upon enrollment
Fashion Discount: 30% discount on merchandise in-store or online (excluding Trendsend); additional eligibility for 30% discount online and in-store at Jaxen Grey
Flexible Work Model: work from home flexibility with 4-day in-office presence to build connection with team members

Role Overview

Reports to: Chief Digital Officer
Level: 6
Location: Edina, MN headquarters (onsite; not remote)

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1mo ago

Principal Product Manager, Experimentation & Digital Analytics

GEICO Bethesda, MD

Bethesda, MD

1mo ago Closed

$147k - $230k/yr Full time Data Analytics Digital Analytics Experimentation

This position is no longer accepting applications (closed Sep 24, 2026).

Job Description

GEICO is hiring a Principal Product Manager to own experimentation and digital analytics platforms that support data-driven decision making across the organization. This hybrid role in Bethesda, MD helps scale self-service experimentation and rigorous analysis, so teams can move faster while maintaining statistical integrity. If you enjoy building platforms that strengthen trust in outcomes and enable teams to act on high-quality evidence, this role is built for that.

What you’ll do

Own the product vision, strategy, and roadmap for GEICO’s experimentation and digital analytics platforms, aligned to growth, retention, and digital transformation goals.
Drive adoption of experimentation and digital analytics tools across product, design, engineering, marketing, and analytics teams, reducing friction and strengthening confidence in platform outputs.
Enable self-service and automation for experiment design, instrumentation, execution, analysis, and reporting to reduce reliance on manual and ad hoc processes.
Define and evolve standards, guardrails, and governance for experimentation, including statistical methodology, sample size and power, metric definitions, guardrail metrics, and peer review, to ensure decisions are grounded in rigorous, causally sound evidence.
Partner with data science, engineering, and analytics leaders to shape architecture, instrumentation strategy, and measurement pipelines for experimentation and digital analytics at scale.
Lead cross-functional teams across the product lifecycle for platform capabilities, from concept through launch and beyond.
Conduct research with platform users (product managers, analysts, data scientists, engineers) to identify friction points, unmet needs, and high-leverage improvements to experimentation velocity and insight quality.
Prioritize initiatives using user feedback, business impact, and technical feasibility, making trade-off decisions as needed.
Drive delivery by defining requirements, managing backlog, and ensuring high-quality releases.
Set north-star metrics and KPI trees for platform health and impact (experiment velocity, coverage, time-to-insight, adoption, decision quality) and continuously monitor and iterate.
Champion a culture of experimentation through enablement, training, evangelism, and demonstrated business impact.
Collaborate with stakeholders to build alignment on platform strategy, prioritization, and investment.
Identify options and recommendations while working through trade-offs to remove impediments for the team.
Oversee platform rollout plans, segment user needs across teams, and promote adoption and best practices.
Partner with Data & Technology leaders to influence end-state architecture and drive secure, resilient, performant, and scalable platform solutions for material customer and business problems.

Requirements

Bachelor’s degree in a quantitative field (e.g., Statistics, Mathematics, Economics, Computer Science, Engineering) strongly preferred.
10+ years of experience in product management, including significant ownership of platform, tools, or data/analytics products used broadly across an organization.
Experience building, scaling, or leading an experimentation program or platform (e.g., A/B testing infrastructure, feature flagging, causal measurement) at meaningful scale.
Strong analytical and statistical foundation, with hands-on fluency in experimental design and statistical inference (hypothesis testing, statistical power, confidence intervals, false discovery/positive control, variance reduction).
Proven track record driving adoption of self-service tools or platforms and measurably improving the velocity and quality of decision-making across teams.
Hands-on experience analyzing large datasets and making causally grounded decisions.
Leadership skills to influence stakeholders and inspire cross-functional teams without direct authority.
Excellent communication and presentation skills to explain complex statistical and technical concepts to technical and non-technical audiences.
Experience working with Agile methodologies and tools such as JIRA or Azure DevOps.
Passion for innovation, continuous learning, and driving positive change.

Preferred qualifications

Advanced degree (MS or PhD) in Statistics, Economics, Data Science, Computer Science, or a related quantitative field.
Direct experience owning or building an experimentation or digital analytics platform (e.g., feature flagging and rollout systems, A/B testing platforms, session replay/behavioral analytics tools, or internal frameworks), commercial or homegrown.
Deep expertise in causal inference and applied statistics (power analysis, sequential testing, variance reduction such as CUPED, heterogeneous treatment effects, quasi-experimental methods like difference-in-differences or synthetic controls).
Experience defining and evolving experimentation governance including metric standards, guardrails, peer review processes, and centers of excellence.
Hands-on fluency in SQL, Python, and/or R, plus experience defining instrumentation and event schemas for digital analytics.
Experience with digital behavioral analytics tools (e.g., clickstream, session replay, funnel and journey analysis) and connecting quantitative insight to qualitative customer understanding.
Experience building enablement programs, training curricula, or centers of excellence that scaled a data-driven or experimentation culture across a large organization.
Experience in insurance, financial services, or another highly regulated industry.
Familiarity with model evaluation, monitoring, and experimentation practices for ML-driven or personalization systems.
MBA, MS, or technical degree a plus.

Technologies

JIRA
Azure DevOps
SQL
Python
R

Benefits

Competitive pay, benefits, and flexibility to support well-being and your future.
Personalized development programs, mentorship, and certification assistance.

Additional details

Location: Bethesda, MD (hybrid). On-site presence required 2-3 days a week.
Work locations listed for the hybrid role: Palo Alto, CA; Seattle, WA; Bethesda, MD.
GEICO Pledge: Great Company, Great Culture, Great Rewards, and Great Careers.
Salary: Annual $146,575.00 - $229,600.00.
Employment authorization: GEICO will not sponsor a new applicant for employment authorization for this position.

Compensation note: Annual salary range listed is $146,575.00 - $229,600.00.

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