Staff Fraud and Risk Analyst
Intuit
Job Overview
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Job Description
Overview
One out of every two small businesses fail within their first five years, most often due to running out of cash. Intuit QuickBooks is on a mission to provide small businesses access to all the tools they need to manage cashflow. We leverage the rich data inside QuickBooks to enable super-fast payments, payroll, and access to capital. With QuickBooks, America’s entrepreneurs never again have to worry about not making payroll or saying no to a business opportunity. That’s how we power prosperity around the world.
We are seeking a Staff Fraud and Risk Analyst as part of our growing Risk Analytics and Insight team within Intuit’s Global Business & Self-Employed Group (GBSG). The successful analyst will work across functions (Fraud & Risk Operations, Data Science, Compliance, Marketing, Product, Finance, etc.) and use data to drive insights which help achieve Intuit Small Business Group’s short and long-term business outcomes.
This role will focus on collaborating with a large Risk Operations team and Risk policy analysts to evaluate existing risk policies for fraud, financial and compliance risk mitigation, evaluating existing manual risk case review processes to drive operational efficiency and find ways to scale our internal processes for business and customer growth. Responsibilities will primarily focus on measuring effectiveness and efficiency of our risk policies and risk operational processes related to agent/ manual case reviews. Successful candidates for this role will leverage risk expertise, financial analytics and innovative risk strategies to enable Intuit’s SMB growth and expansion, achieve optimal profitability, while keeping operational costs low and enhance trust-related merchant and consumer experience.
Responsibilities
- Ability to analyze & research large data sets, develop insights and translate insights into business opportunities/requirements.
- Develop compelling visualizations for story telling that crystallize business opportunities for stakeholders and leaders to make timely decisions.
- Understand various aspects of Risk Operations in detail and build comprehensive KPIs to monitor performance.
- Design, implement, and monitor experiments to explore new methodologies and estimate key metrics for risk operational processes effectiveness and efficiency.
- Ability to perform quantitative and business trade off decisions to improve risk operation processes to mitigate Risk in payments, payroll and capital loan products.
- Effectively able to work with product and technology teams to build risk solutions and collaborate with risk operations to operationalize solutions and get feedback.
- Ability to work with data engineers and technology teams to enhance/ enrich our data ecosystem/ risk data marts.
- Deliver ideas and insights as you collaborate with partner teams, such as engineering, data science & operations to build risk detection systems that drive overall efficiency, Customer Experience And Agent Investigation Capabilities.
- In addition, the candidate should bring a high level of enthusiasm to the projects and the ability to organize and motivate large groups. This includes taking initiative, ownership and responsibility for a project
- Team player with experience working on cross functional. Must have good judgement with the ability to think creatively and strategically while working on multiple key projects simultaneously.
Qualifications
- Strong analytical ability and proven business acumen with at least 2 years of relevant Experience. Experience In Financial Services Or FinTech Highly Preferred.
- Advanced SQL, Python and coding skills to perform data segmentation and aggregation from scratch.
- Good working experience with data analytics and visualization tools like Tableau and Quicksight
- Excellent written and verbal communication skills.
- High degree of accountability, organization and empathy.
- Experience working with Key Performance Indicator (KPI or OKR) metrics.
- Passion for analyzing data and an insatiable curiosity to understand complex business issues and proactively looking for business opportunities and drive new innovations
- Ability to tell stories with data, identify key insights and support data-driven decision making for our stakeholders
- Able to work in a fast-paced working environment, multitask, balancing short & long term strategic implications to meet or exceed business objectives
- Bachelor’s Degree in Economics, Science, Math or other Quantitative Field, or commensurate experience. An MBA or graduate degree in a related field is a plus or equivalent experience.
Compensation & Benefits
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). 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: New York: $168,500 - $228,000
Key skills/competency
- Fraud detection
- Risk mitigation
- Data analysis
- Policy evaluation
- Operational efficiency
- Financial analytics
- KPI monitoring
- Experiment design
- Cross-functional collaboration
- Customer experience
How to Get Hired at Intuit
- Research Intuit's culture: Study their mission, values, recent news, and employee testimonials on LinkedIn and Glassdoor.
- Tailor your resume: Highlight fraud, risk analytics, FinTech experience, and proficiency in SQL, Python, and visualization tools.
- Showcase analytical prowess: Prepare to discuss past projects involving data segmentation, insights generation, and experiment design.
- Practice behavioral questions: Focus on demonstrating collaboration, problem-solving, and managing multiple strategic projects.
- Network within Intuit: Connect with current employees in risk, data science, or analytics teams for informational interviews.
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