Guidehouse is a leading global provider of consulting services to the public and commercial markets with broad capabilities in management, technology, and risk consulting. We help clients address their toughest challenges and navigate significant regulatory pressures with a focus on transformational change, business resiliency, and technology-driven innovation. Across a range of advisory, consulting, outsourcing, and digital services, we create scalable, innovative solutions that prepare our clients for future growth and success. The company has more than 10,000 professionals in over 50 locations globally. Guidehouse is a Veritas Capital portfolio company, led by seasoned professionals with proven and diverse expertise in traditional and emerging technologies, markets, and agenda-setting issues driving national and global economies. For more information, please visit: www.guidehouse.com.
Responsibilities
- Apply statistical and programming skills to convert raw data into insights that help clients understand and mitigate fraud threats.
- Analyze the effectiveness of existing fraud models and oversee the design, development, and management of new real-time fraud rules and models.
- Research and apply the latest machine learning algorithms to power analytical solutions for managing fraud problems in the market.
- Collaborate with clients and domain experts to drive the development and optimization of machine learning fraud models.
- Responsible for day-to-day activities of a project including interaction with other team members, professionals from other firms involved in the engagement, and client personnel.
- Own data science areas such from analytics roadmap and prioritization to definition of KPIs and developing new ways of understanding customer feature engagement.
- Prepare reports, written analyses, quantitative exhibits, and other client deliverables regarding projects and/or results of work performed.
Qualifications
Required:
- Advanced degree from an accredited college/university.
- 3+ years of experience as a Data Scientist or Data Analyst.
- Strong proficiency with big data technologies (e.g. SQL, Spark, Python).
- Solid experience in Data Science, Predictive modeling, exploratory analytics.
- Experience in experimentation design, A/B testing, propensity score analysis, linear regression and/or probabilistic modeling.
- Fluency in Microsoft SQL Server.
- Fluency in programming languages, e.g., R, Python, etc.
- Experience analyzing and visualizing data.
- Experience with visualization of data including Tibco Spotfire, Tableau, R, PowerPivot, PowerBI, Excel, and others
- Strong conceptual as well as quantitative and qualitative analytical skills.
- Intellectual curiosity and the ability to ask probing, thoughtful questions and examine data from all angles/perspectives.
- Strong team management skills to manage team’s progress and perform quality assurance/quality control of deliverables.
- Ability to take on projects with a sense of ownership and entrepreneurial approach.
- Able to manage several projects simultaneously and autonomously.
Preferred:
- Local to NYC or DC (but not required).
- Experience in a management consulting/advisory company.
- Experience with data visualization tools such as Tableau.
- Experience with Financial Crimes datasets, including third-party and open data sources.