Remote Data Scientist - Fraud Analytics | WFH

Join a Dynamic Team of Innovators

We invite you to take the next step in your career with a leading organization that prioritizes a people-oriented and client-focused approach. As a vital member of our team, you will contribute to our mission of empowering businesses and individuals to flourish today, tomorrow, and into the future. Our community of forward-thinking professionals is dedicated to achieving results with uncompromising integrity, working collectively to enhance the health and wealth journey for all.

Empower Your Career with Us

We are committed to attracting top-tier talent! While we offer positions in our office locations, we are excited to provide remote opportunities across numerous states, including AL, AZ, FL, GA, IA, IL, IN, MI, MN, MO, NC, NE, PA, SC, TN, TX, UT, VA, and WV. Please be aware that the remote status and roles may change, and we do not provide relocation assistance.

Your Unique Skills Matter

We encourage applications from individuals who may not meet every requirement. Our goal is to cultivate an inclusive workplace that values diversity. If you excel in a collaborative and engaging environment that promotes professional growth, we would love to hear from you! We eagerly anticipate your application.

Key Responsibilities

• Utilize advanced data science methodologies to combat fraud in consumer-facing SaaS applications, addressing critical questions that inform fraud risk management decisions.
• Develop and execute sophisticated analytics models for fraud detection, leveraging machine learning and statistical techniques.
• Analyze extensive transactional datasets to uncover patterns and trends indicative of fraudulent activities.
• Design and implement real-time fraud monitoring systems to identify suspicious behaviors.
• Establish processes to assess and enhance model performance continuously.
• Collaborate with Compliance and Security teams to facilitate data-driven decision-making.
• Generate key performance indicators for fraud protection to report to operational risk teams and senior management.
• Design and refine algorithms for matching and pattern recognition using cutting-edge methodologies.
• Partner with business and risk teams to optimize risk metrics, assessment techniques, and indicators for evaluating the overall risk landscape.
• Conduct holistic evaluations of fraud cases to determine areas for improvement.
• Prepare and present analytic findings and solutions to internal stakeholders.
• Translate business needs into actionable analytic projects in collaboration with internal teams.
• Lead projects from conception through completion.
• Stay updated on the latest trends, regulations, and issues in the Fraud/Risk sector.
• Compile and analyze information from academic publications, market analysis, and reports to ensure current, cutting-edge knowledge.
• Contribute actively to the overarching Insights strategy.
• Perform additional duties as assigned.
  
  

Essential Qualifications

• 7-10 years of experience in Data Science, Statistics, or related fields.
• Master's Degree in Statistics, Mathematics, Computer Science, Engineering, or Data Science.
• Specialization in Fraud Analytics with a minimum of 3 years of relevant experience.
  
  

Required Skills

• Proficient in programming languages including Python, SQL, and R.
• Familiarity with Docker Containers is advantageous.
• Exceptional analytical skills and a proactive mindset.
• Strong organizational capabilities with a focus on meeting deadlines.
• Emphasis on precision and efficiency in work processes.
• Proficient in Microsoft Excel, Word (including mail merge), and Outlook.
• Excellent verbal and written communication skills.
• Ability to prioritize and manage multiple tasks efficiently.
• Strong collaboration abilities and eagerness to learn and apply new concepts swiftly.
• Experience with Salesforce CRM is preferred.
  
  

We look forward to the possibility of you joining our team, where you will play a key role in shaping innovative solutions and fostering a culture of excellence.

Employment Type: Full-Time