Sr/Principal Data Scientist, Risk Strategy

Unchain Data; San Jose (CA); On-site; USD 223,661 - 313,055; Full time

Benefits offered by this job

L&D programs

Wellness and meal allowances

Competitive total compensation package

Job summary

Unchain Data in San Jose, California, is seeking a Sr Data Scientist to leverage analytical expertise in fraud analytics. The role involves utilizing machine learning techniques to identify complex fraud patterns and providing technical guidance across teams.

The ideal candidate will have a Master's degree and at least 4 years of relevant experience in financial services or FinTechs. A competitive compensation package, including salary and performance bonuses, is offered.

Qualifications

• 4+ years of fraud analytics experience in financial services or FinTechs.
• Deep understanding of modern machine learning techniques and algorithms.
• Experience in a fast-paced startup environment.

Responsibilities

• Identify complex fraud patterns through data mining and analysis.
• Serve as technical SME by sharing new data mining techniques.
• Collaborate to communicate analytical findings to stakeholders.

Skills

Fraud analytics experience

Machine learning techniques

Statistical programming (SQL, R, Python)

Project management skills

Communication (written and verbal)

Education

Master's degree or PhD in relevant field

Tools

SQL

R

Python

Job description

About the Opportunity

The Sr Data Scientist, Risk will offer a strategic perspective, deep analytical and modeling capabilities, and a collaborative working style. The right candidate will have strong intellectual curiosity and passion for achieving business results. An ability to quickly define the problem, research and leverage state-of-the-art modeling techniques, and provide timely recommendations will be essential. Key skills will include a strong analytical mindset, deep understanding of most popular machine learning algorithms and lead key initiatives with integrity and a passion for investigations, problem solving, and troubleshooting.

Responsibilities

• Identify complex fraud patterns and their technical root causes through detailed data mining and analysis, including identification of sophisticated fraud methods employed by actors who are deliberately trying to avoid detection.
• Serve as technical SME by sharing new data mining techniques, maintaining technical reference documentation, and interfacing with partner technology teams.
• Collaborate across business and technology stakeholders to communicate analytical findings to both technical and non-technical audiences.
• Provide technical guidance for engineering projects that incorporate new data points into the investigation team's toolkit, such as API integrations or internal data transformations.
• Link Analysis/Graph analytics to find and mitigate deeply-connected fraud networks and detect new accounts being added to these networks.
• Apply unsupervised learning methods to augment existing supervised models, or detect portfolio anomalies.
• Development of machine learning models.
• Partner with product and engineering team in implementing features and models, and enhancing systems.

Requirements

• Master's degree (or PhD) in Statistics, Mathematics, Operations Research, Computer Science, Economics, Engineering or other quantitative discipline. Bachelor's degree with significant relevant experience will be considered.
• 4+ years of fraud analytics experience in financial services or FinTechs.
• Crypto/Blockchain experience.
• Deep understanding of modern machine learning techniques and algorithms including GBM, XGBoost, LGBM, etc.
• Advanced programming skills in statistical and analytical software (SQL, R, Python, etc.).
• Successful track record of owning and driving large, complex data analysis projects.
• Demonstrated capacity for innovation and outside-the-box thinking in the creation of new capabilities and processes that are unstructured or exploratory in nature.
• Experience in a fast-paced startup environment with a strong level of initiative.
• Ability and willingness to travel as needed.
• Strong communicator in both writing and speaking.
• Multi-tasking and strong project management skills.

Nice to Have

• Hands-on experience and knowledge of modeling in machine learning (GBM, XGBoost, Random Forest, etc.).

Benefits

• Competitive total compensation package.
• L&D programs and Education subsidy for employees' growth and development.
• Various team building programs and company events.
• Wellness and meal allowances.
• Comprehensive healthcare schemes for employees and dependants.

Compensation

The salary range for this position is $223,661.00 to $313,055.00. The salary offered depends on a variety of factors, including job-related knowledge, skills, experience, and market location. In addition to the salary, a performance bonus and long-term incentives may be provided as part of the compensation package, as well as a full range of medical, financial, and/or other benefits, dependent on the position offered.