Remote opens the vast potential of the world for every person, business, and country, building a world where every person and business truly belongs. We empower companies of all sizes to pay and manage full-time and contract workers around the world. Remote makes it easy to manage international payroll, benefits, taxes, stock options, and compliance in 50...

Read more about this company

Director, Marketing Analytics

Job Type

Full Time

Qualification

BA/BSc/HND

Experience

10 years

Location

Nairobi

Job Field

Data, Business Analysis and AI , ICT / Computer

We are looking for an experienced Marketing Analytics Director, who is able to help us deepen our funnel understanding, build robust measurement capabilities, bring to life an incrementality mindset, enhance forecast accuracy, build a ‘next best dollar’ capability, and build industry-leading predictive models to help us better meet our customers’ needs and enhance the effectiveness of our spend.

What you bring

Experience:

10+ years in Marketing Analytics, Business Intelligence, or Data Science, with at least 3 years in a leadership role.

Expert-level Technical Stack Knowledge:

Expertise in SQL and Python/R for data manipulation.

Proficiency with visualization tools like Tableau, Looker, or Power BI.

Deep experience with Google Analytics 4, Google Tag Manager, and CRM data (Salesforce/HubSpot).

Ability to use data to make decisions, think at scale, and implement repeatable processes.

Mathematical Prowess:

Strong grasp of statistical concepts like significance testing, regression analysis, and experimental design (A/B testing).

Data Science Foundations:

Deep understanding of statistical modelling, specifically as it applies to marketing (Bayesian methods for MMM, Random Forests for churn, etc.).

Industry Knowledge:

Proven track record in SaaS or B2B marketing analytics, with knowledge of the MarTech Ecosystem: Expert understanding of signal loss — how iOS14+, cookie deprecation, and privacy regulations impact our ability to track and target.

Communication:

Exceptional written and verbal communication skills; ability to explain complex technical solutions to non-technical stakeholders clearly.

Management:

Proven track record of managing high-performing analysts and data scientists.

Mindset:

A "bias toward action" and a passion for continuous improvement in a fluid, high-growth environment.

Language:

Fluent English (written and spoken)

Key Responsibilities

Strategic Leadership:

Develop the long-term vision for marketing analytics, ensuring data infrastructure supports business goals.

Measurement & Attribution:

Design and manage sophisticated multi-touch attribution (MTA) models and Media Mix Modelling (MMM) to evaluate the effectiveness of all channels.

Predictive Intelligence:

Shift the team from reactive reporting to predictive modelling. Lead the development of churn propensity models and lead scoring algorithms that directly feed into our automation platforms.

Testing & Experimentation:

Champion a test & learn culture. Design the roadmap for geo-holdout tests, A/B testing, and multivariate experiments to prove incrementality.

Budget Optimization:

Partner with the growth team to allocate a multi-million dollar budget, using predictive modelling to maximize ROAS.

Customer Insights:

Oversee cohort analysis, LTV (Lifetime Value) projections, and churn prediction models to deepen our understanding of the customer journey.

Dashboarding & Reporting:

Build and maintain automated executive-level dashboards that provide real-time visibility into KPI performance.

Stakeholder Influence:

Act as a strategic advisor to the Performance, Brand, and Product Marketing leads, helping them use data to justify their budgets and pivot strategies in real-time.

Team Management:

Mentor and grow a team of marketing analysts, fostering a culture of curiosity and technical excellence.

Cross-Functional Collaboration:

Act as the liaison between Marketing, Data Engineering, Revenue Operations and Finance to ensure a single source of truth for marketing data.

• Develop the long-term vision for marketing analytics, ensuring data infrastructure supports business goals.
• Design and manage sophisticated multi-touch attribution (MTA) models and Media Mix Modelling (MMM) to evaluate the effectiveness of all channels.
• Shift the team from reactive reporting to predictive modelling. Lead the development of churn propensity models and lead scoring algorithms that directly feed into our automation platforms.
• Champion a test & learn culture. Design the roadmap for geo-holdout tests, A/B testing, and multivariate experiments to prove incrementality.
• Partner with the growth team to allocate a multi-million dollar budget, using predictive modelling to maximize ROAS.
• Oversee cohort analysis, LTV (Lifetime Value) projections, and churn prediction models to deepen our understanding of the customer journey.
• Build and maintain automated executive-level dashboards that provide real-time visibility into KPI performance.
• Act as a strategic advisor to the Performance, Brand, and Product Marketing leads, helping them use data to justify their budgets and pivot strategies in real-time.
• Mentor and grow a team of marketing analysts, fostering a culture of curiosity and technical excellence.
• Act as the liaison between Marketing, Data Engineering, Revenue Operations and Finance to ensure a single source of truth for marketing data.

• SQL
• Python/R
• Tableau
• Looker
• Power BI
• Google Analytics 4
• Google Tag Manager
• CRM data (Salesforce/HubSpot)
• Statistical concepts (significance testing, regression analysis, experimental design)
• Statistical modelling (Bayesian methods for MMM, Random Forests for churn)
• MarTech Ecosystem knowledge
• Written and verbal communication skills
• Leadership

• 10+ years in Marketing Analytics, Business Intelligence, or Data Science
• At least 3 years in a leadership role
• Expert-level Technical Stack Knowledge
• Proficiency with visualization tools
• Deep experience with Google Analytics 4, Google Tag Manager, and CRM data
• Ability to use data to make decisions, think at scale, and implement repeatable processes
• Strong grasp of statistical concepts
• Deep understanding of statistical modelling
• Proven track record in SaaS or B2B marketing analytics
• Exceptional written and verbal communication skills
• Proven track record of managing high-performing analysts and data scientists
• A "bias toward action" and a passion for continuous improvement
• Fluent English (written and spoken)