Intuit
Overview
Intuit's Global Business Solutions Group (GBSG) is dedicated to powering prosperity for small and mid-sized businesses (SMBs) through data-driven innovation that simplifies how they move and manage their money. At the center of this mission, the
Payments team
enables seamless, trusted money movement experiences that help customers get paid faster and manage cash flow with confidence.
The
Payments Data Science & Analytics
team plays a pivotal role in this vision by developing insights, models, and scalable analytics solutions that fuel growth, efficiency, and world-class customer experiences across Intuit's Payments ecosystem. This leader will sit within the
GBSG Data Science & Analytics organization
, partnering closely with the
Payments cross-functional leadership team
within Intuit's
Services organization
to drive impact across Product, Marketing, Engineering, and Operations.
The
Group Manager, Data Science & Analytics
will lead a team of senior data scientists, analysts, and people managers to define the strategy, vision, and roadmap for Payments data science. This leader will champion the use of AI and advanced analytics to identify growth opportunities, optimize risk and revenue, and enhance customer trust - all while fostering a high-performance, customer-obsessed culture.
Responsibilities
Lead and scale
a high-performing team of data scientists, analysts, and data science managers to deliver end-to-end insights and modeling solutions that accelerate Payments growth, efficiency, and customer satisfaction.
Develop and execute
the strategic vision for Payments analytics, aligning data science priorities with GBSG's business strategy and Intuit's broader AI-driven expert platform goals.
Partner with Payments product, engineering, and marketing leaders
to deliver insights that improve customer acquisition, onboarding, retention, and lifetime value - balancing growth with risk management.
Drive predictive and generative AI innovation
, including applications for customer segmentation, transaction forecasting, fraud mitigation, and personalized experiences.
Own and evolve measurement frameworks
for key business and customer outcomes, including growth, profitability, risk, and customer experience metrics.
Champion experimentation and data-driven decision-making
, using hypothesis-driven analysis to uncover opportunities for step-change improvements in payments conversion, authorization rates, and customer satisfaction.
Serve as a thought partner
to Payments and GBSG executives, influencing strategic decisions through compelling storytelling and actionable data narratives.
Foster a culture of inclusion, innovation, and continuous improvement
, empowering teams to deliver measurable business impact and grow their careers within a dynamic, fast-paced environment.
Collaborate cross-functionally
across Intuit's ecosystem (Product, Customer Success, Risk, Finance, Marketing, and Design) to deliver shared success metrics and advance enterprise-wide data maturity.
Qualifications
Qualifications
12+ years of experience
in data science, analytics, or related quantitative disciplines;
6+ years of people leadership experience
, including leading other managers and senior ICs.
Proven ability to
define and execute data science strategies
that deliver measurable business growth, revenue impact, and customer benefit.
Deep experience with
payments, fintech, or financial services
, including familiarity with customer lifecycle analytics, transaction data, and risk modeling.
Demonstrated expertise in
supervised and unsupervised learning
, experimentation design, and advanced statistical modeling.
Track record of
influencing senior executives
and partnering across functions to align on shared business goals and KPIs.
Strong background in
data storytelling
, translating complex quantitative findings into clear, actionable recommendations.
Passion for
developing talent
, building high-performing, diverse teams, and advancing analytics maturity within large organizations.
Extreme ownership mindset with operational rigor, adaptability, and a focus on business outcomes.
Technical Skills
Proficiency in
SQL
,
Python
,
R
, and data visualization tools (Tableau, Qlik, Looker, or equivalent).
Expertise in
machine learning
and
predictive analytics
, including experience with classification, regression, clustering, and embedding models.
Strong understanding of
data infrastructure and pipelines
supporting large-scale data products.
Familiarity with
modern AI/ML techniques
(e.g., LLMs, reinforcement learning, generative AI) and their application to customer and operational use cases.
Experience working with
cloud-based data ecosystems
(AWS, Snowflake, or GCP).
Preferred Qualifications
Experience leading analytics or data science teams in
payments, fintech, or SaaS
industries.
Proven success in developing
reusable analytics frameworks
and tools that enable scale and self-service across functions.
Familiarity with
risk and compliance analytics
, including fraud detection and loss prevention modeling.
Demonstrated ability to
accelerate innovation
through AI and automation, translating insights into measurable product and customer outcomes.
Strong understanding of
financial performance metrics
(revenue, margins, cost-to-serve) and ability to link data insights to business P&L.
Intuit provides a competitive compensation package with a strong pay for performance rewards approach. This position will be eligible for a cash bonus, equity rewards and benefits, in accordance with our applicable plans and programs (see more about our compensation and benefits at Intuit®: Careers | Benefits (https://www.intuit.com/careers/benefits/full-time-employees/) ). Pay offered is based on factors such as job-related knowledge, skills, experience, and work location. To drive ongoing fair pay for employees, Intuit conducts regular comparisons across categories of ethnicity and gender. The expected base pay range for this position is:
EOE AA M/F/Vet/Disability. Intuit will consider for employment qualified applicants with criminal histories in a manner consistent with requirements of local law.
Intuit's Global Business Solutions Group (GBSG) is dedicated to powering prosperity for small and mid-sized businesses (SMBs) through data-driven innovation that simplifies how they move and manage their money. At the center of this mission, the
Payments team
enables seamless, trusted money movement experiences that help customers get paid faster and manage cash flow with confidence.
The
Payments Data Science & Analytics
team plays a pivotal role in this vision by developing insights, models, and scalable analytics solutions that fuel growth, efficiency, and world-class customer experiences across Intuit's Payments ecosystem. This leader will sit within the
GBSG Data Science & Analytics organization
, partnering closely with the
Payments cross-functional leadership team
within Intuit's
Services organization
to drive impact across Product, Marketing, Engineering, and Operations.
The
Group Manager, Data Science & Analytics
will lead a team of senior data scientists, analysts, and people managers to define the strategy, vision, and roadmap for Payments data science. This leader will champion the use of AI and advanced analytics to identify growth opportunities, optimize risk and revenue, and enhance customer trust - all while fostering a high-performance, customer-obsessed culture.
Responsibilities
Lead and scale
a high-performing team of data scientists, analysts, and data science managers to deliver end-to-end insights and modeling solutions that accelerate Payments growth, efficiency, and customer satisfaction.
Develop and execute
the strategic vision for Payments analytics, aligning data science priorities with GBSG's business strategy and Intuit's broader AI-driven expert platform goals.
Partner with Payments product, engineering, and marketing leaders
to deliver insights that improve customer acquisition, onboarding, retention, and lifetime value - balancing growth with risk management.
Drive predictive and generative AI innovation
, including applications for customer segmentation, transaction forecasting, fraud mitigation, and personalized experiences.
Own and evolve measurement frameworks
for key business and customer outcomes, including growth, profitability, risk, and customer experience metrics.
Champion experimentation and data-driven decision-making
, using hypothesis-driven analysis to uncover opportunities for step-change improvements in payments conversion, authorization rates, and customer satisfaction.
Serve as a thought partner
to Payments and GBSG executives, influencing strategic decisions through compelling storytelling and actionable data narratives.
Foster a culture of inclusion, innovation, and continuous improvement
, empowering teams to deliver measurable business impact and grow their careers within a dynamic, fast-paced environment.
Collaborate cross-functionally
across Intuit's ecosystem (Product, Customer Success, Risk, Finance, Marketing, and Design) to deliver shared success metrics and advance enterprise-wide data maturity.
Qualifications
Qualifications
12+ years of experience
in data science, analytics, or related quantitative disciplines;
6+ years of people leadership experience
, including leading other managers and senior ICs.
Proven ability to
define and execute data science strategies
that deliver measurable business growth, revenue impact, and customer benefit.
Deep experience with
payments, fintech, or financial services
, including familiarity with customer lifecycle analytics, transaction data, and risk modeling.
Demonstrated expertise in
supervised and unsupervised learning
, experimentation design, and advanced statistical modeling.
Track record of
influencing senior executives
and partnering across functions to align on shared business goals and KPIs.
Strong background in
data storytelling
, translating complex quantitative findings into clear, actionable recommendations.
Passion for
developing talent
, building high-performing, diverse teams, and advancing analytics maturity within large organizations.
Extreme ownership mindset with operational rigor, adaptability, and a focus on business outcomes.
Technical Skills
Proficiency in
SQL
,
Python
,
R
, and data visualization tools (Tableau, Qlik, Looker, or equivalent).
Expertise in
machine learning
and
predictive analytics
, including experience with classification, regression, clustering, and embedding models.
Strong understanding of
data infrastructure and pipelines
supporting large-scale data products.
Familiarity with
modern AI/ML techniques
(e.g., LLMs, reinforcement learning, generative AI) and their application to customer and operational use cases.
Experience working with
cloud-based data ecosystems
(AWS, Snowflake, or GCP).
Preferred Qualifications
Experience leading analytics or data science teams in
payments, fintech, or SaaS
industries.
Proven success in developing
reusable analytics frameworks
and tools that enable scale and self-service across functions.
Familiarity with
risk and compliance analytics
, including fraud detection and loss prevention modeling.
Demonstrated ability to
accelerate innovation
through AI and automation, translating insights into measurable product and customer outcomes.
Strong understanding of
financial performance metrics
(revenue, margins, cost-to-serve) and ability to link data insights to business P&L.
Intuit provides a competitive compensation package with a strong pay for performance rewards approach. This position will be eligible for a cash bonus, equity rewards and benefits, in accordance with our applicable plans and programs (see more about our compensation and benefits at Intuit®: Careers | Benefits (https://www.intuit.com/careers/benefits/full-time-employees/) ). Pay offered is based on factors such as job-related knowledge, skills, experience, and work location. To drive ongoing fair pay for employees, Intuit conducts regular comparisons across categories of ethnicity and gender. The expected base pay range for this position is:
EOE AA M/F/Vet/Disability. Intuit will consider for employment qualified applicants with criminal histories in a manner consistent with requirements of local law.