
501 - 1000 employees
Founded 2015
đź Consulting
âď¸ Legal
đŚ Logistics
đ° $30M Series B - Sumsub on 2022-12
Consulting ⢠Legal ⢠Logistics
Sumsub is a compliance-focused technology company that provides SaaS solutions for transaction monitoring, product compliance, and related operational and pre-sales support to businesses. The company appears to operate an online platform with roles across operations, legal/compliance, and technical support, and targets other businesses with its services and tools.
đ September 29
Where this job comes from
Posted on Sumsub's careers page â, not through a job board
First seen by Remote Rocketship September 29
Still open on Sumsub's site. Checked 9 hours ago.

501 - 1000 employees
Founded 2015
đź Consulting
âď¸ Legal
đŚ Logistics
đ° $30M Series B - Sumsub on 2022-12
Consulting ⢠Legal ⢠Logistics
Sumsub is a compliance-focused technology company that provides SaaS solutions for transaction monitoring, product compliance, and related operational and pre-sales support to businesses. The company appears to operate an online platform with roles across operations, legal/compliance, and technical support, and targets other businesses with its services and tools.
⢠Investigate live data to identify emerging fraud patterns, anomalous activity, and gaps in detection logic ⢠Develop and tune fraud detection approaches using rules, supervised and unsupervised models, anomaly detection, and link-based analysis ⢠Evaluate the accuracy, completeness, and predictive value of fraud signals ⢠Analyze client traffic and alert flows ⢠Measure false positives and missed fraud and recommend concrete improvements ⢠Build and optimize baseline rule sets and proactive alerts for common and emerging fraud scenarios ⢠Turn analytical findings into clear product recommendations ⢠Support complex, data-intensive client cases when needed
⢠4+ years of experience in anti-fraud, risk analytics, applied data science, or another analytical role involving complex data and anomaly detection ⢠Strong knowledge of exploratory data analysis and classical machine learning, including supervised and unsupervised approaches ⢠Practical experience with anomaly detection, clustering, and link-based or graph analysis ⢠Hands-on experience in fraud prevention or fraud analytics ⢠Strong Python and SQL skills ⢠Hands-on experience with ClickHouse, Trino, Superset, dbt, DataHub, or comparable analytics tools ⢠Ability to identify data-quality issues, bias, leakage, overfitting, and misleading model results ⢠Ability to evaluate detection quality through false positives, false negatives, and other relevant metrics ⢠Ability to explain complex findings through clear logic, numbers, and concrete examples ⢠Confident but critical use of AI-assisted analytical tools, including the ability to validate their outputs ⢠Fluency in English
⢠Remote-first, trust-based culture with no mandatory office days or attendance trackers ⢠Choice of offices or coworking spaces in some locations ⢠Flexible working hours without a fixed 9-to-5 schedule ⢠Birthday holiday ⢠10 personal days each year ⢠Seven sick days without paperwork ⢠Extra time off for Christmas and New Year ⢠Role-specific learning opportunities and covered professional events ⢠Financial bonuses for marriage and welcoming a new baby ⢠Fully covered team offsite trips several times a year ⢠Tools and hardware needed to perform the work
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