Stop burning months on recruiting — start blocking fraud tomorrow. Outstaffed Python developers give you instant access to niche expertise in wallet clustering, AML heuristics, and real-time anomaly detection without adding permanent headcount.
• Pay only for active work — no payroll tax, no benefits.
• Swap or scale engineers in days as threat models evolve.
• Proven crypto security know-how from dozens of exchanges baked in from day one.
Compared with direct hiring, Smartbrain manages vetting, compliance, equipment, and retention, so your CTO can stay focused on shipping secure trading features that win market share.
Faster Onboarding
Lower Payroll Costs
Elastic Team Size
Deep Crypto Expertise
24/7 Development Cycle
No Recruitment Fees
Vetted Python Gurus
Zero HR Overhead
IP & NDA Safety
Outcome-Based Billing
Rapid Knowledge Transfer
Global Talent Access
Technical Leaders Trust Our Python Augmentation
“Within 36 hours Smartbrain embedded a Django-savvy engineer who wired our blockchain analytics API into the fraud console. False-positive alerts dropped by 29 %, and my team finally had evenings off.”
Melissa Carter
VP Engineering
ClearWave Markets
The outstaffed developer arrived pre-loaded with NumPy and PySpark playbooks for wash-trading detection. Two-day onboarding, then throughput doubled as legacy scripts were refactored into asynchronous FastAPI services.
David Nguyen
CTO
Catalyst Capital
Smartbrain’s Flask veteran plugged into our micro-service mesh in hours, closing a backlog of AML rules. Quality releases rose 40 % while my permanent staff focused on a new staking feature.
Laura Jenkins
Lead Architect
OrbitEx Exchange
We flexed from 1 to 4 Python contractors during tax season. Pandas-driven reconciliation reports ran 3× faster, and Smartbrain handled every contract and NDA. No legal headaches for us.
Anthony Brooks
Head of Data
LedgerBridge Inc.
Replacing a costly local hire with an outstaffed PyTorch specialist saved 55 % annually. Our new ML classifier now flags mixer-linked addresses with 92 % accuracy.
Sofia Martinez
Fraud Analytics Manager
BluePeak Insurance
Smartbrain’s seasoned Tornado developer built a zero-latency websocket listener that feeds our SIEM. Deployment to Kubernetes was same day, giving us sub-second alerting without touching core staff bandwidth.
Robert Allen
Cybersecurity Director
StellarBank N.A.
Industries We Secure
FinTech Exchanges
FinTech Exchanges lean on Python-driven anomaly engines to spot wash trading, pump-and-dump patterns, and cross-venue spoofing in milliseconds. Augmented developers integrate Chainalysis feeds, build REST & websocket APIs, and optimise pandas pipelines to keep fraud-monitoring dashboards real-time even at peak 50 k TPS volumes.
Traditional Banking
Traditional Banks now custody crypto and must conform to Basel guidelines. Outstaffed Python Devs build ETL jobs that marry SWIFT data with blockchain explorer results, enabling holistic AML analytics and SAR reporting without expanding FTE budgets.
InsurTech
InsurTech carriers use crypto exchange fraud detection algorithms to price cyber-crime policies. Python specialists prototype Monte-Carlo risk models in NumPy, then convert them to performant Cython modules, shortening underwriting cycles and boosting portfolio profitability.
RegTech Providers
RegTech Platforms license turnkey compliance dashboards to exchanges. Augmented engineers craft KYC micro-services, automate SEC & FinCEN reporting, and ensure SOC-2 controls through Python-based test suites.
E-commerce Marketplaces
E-commerce Marketplaces accepting crypto fight refund abuse and chargebacks. Python fraud teams ingest on-chain metadata, correlate with order history, and serve real-time risk scores to checkout pages, cutting loss ratios by double-digits.
Gaming & Gambling
Gaming & Gambling platforms leverage Python signal processing to detect chip-dumping funded with illicit wallets. Augmented developers build ML models in Scikit-learn and push them to cloud functions with latency < 100 ms.
Payment Gateways
Payment Gateways add crypto rails fast by outstaffing. Python engineers integrate Lightning Network nodes, implement AML rulesets, and provide audit-ready logs compliant with PCI-DSS and FATF.
Neo-Banks
Neo-Banks rely on agile Python contractors to pilot new crypto features while core squads chase mobile growth. Fraud modules run on FastAPI and deploy through CI/CD that meets ISO-27001.
Cybersecurity SaaS
Cybersecurity SaaS vendors augment teams with Python developers to extend SIEM connectors, implement blockchain intelligence, and deliver threat-intel feeds that enrich SOC workflows.
Crypto Exchange Fraud Detection Case Studies
Exchange Slash Charge-Back Losses 48 %
Client: Mid-tier US spot & derivatives exchange.
Challenge: rising charge-backs demanded stronger crypto exchange fraud detection with near-real-time wallet analysis.
Solution: A two-member Smartbrain Python squad integrated graph-based address clustering using NetworkX and ported legacy SQL checks to async FastAPI services. The team shipped MVP in 3 weeks and iterated weekly with product managers.
Result: 48 % reduction in fraudulent withdrawals and 38 % faster KYC approval queue, freeing compliance staff to focus on high-risk investigations.
Bank Launches Crypto Desk in 90 Days
Client: Regional commercial bank entering digital-asset custody.
Challenge: meeting OCC audit requirements including crypto exchange fraud detection while lacking blockchain expertise.
Solution: Three Smartbrain Python developers embedded with the bank’s infosec team, building AML pipelines on Apache Airflow and hooking into existing Splunk dashboards. They collaborated with legal to codify rule-sets.
Result: 100 % audit pass rate, crypto desk live in 90 days, and a projected $6 M new fee revenue stream.
Insurance Underwriter Automates Risk Scoring
Client: Fortune-500 InsurTech.
Challenge: manual underwriting slowed by ad-hoc spreadsheets; needed crypto exchange fraud detection at scale.
Solution: Smartbrain supplied a senior data-science-oriented Python engineer who migrated actuarial models to pandas, introduced XGBoost classifiers for wallet behaviour, and containerised the pipeline on AWS Fargate.
Result: 72 % latency reduction in quote generation and 4× analyst throughput, cutting policy issuance time from days to hours.
Book a 15-Minute Call
120+ Python engineers placed, 4.9/5 avg rating. Book vetted talent today and neutralize exchange fraud before the next block is mined.
Specialised Python Services
Real-Time Transaction Monitoring
Augmented Python teams build low-latency websocket listeners, integrate mempool data, and apply ML-based anomaly scoring so exchanges can flag suspicious trades within 200 ms. Businesses get proactive protection without huge CapEx, thanks to outstaffing flexibility.
KYC/AML Automation
Our outstaffed developers craft OCR, sanctions-list screening, and identity-verification micro-services in Django & FastAPI, reducing manual review costs while meeting FinCEN guidelines for crypto compliance.
Blockchain Data Engineering
Python engineers design petabyte-scale ETL pipelines on Spark, ingesting on-chain events into data lakes for investigative queries, letting stakeholders run fraud analytics in seconds instead of hours.
Risk Scoring Algorithms
Seasoned data-science specialists prototype and productionise graph-based wallet clustering, Monte Carlo simulations, and Bayesian fraud models, delivering accurate risk scores that lower charge-back ratios.
Regulatory Reporting Dashboards
We assemble reporting portals that auto-generate SAR, STR, and OFAC reports directly from exchange data, ensuring audit trails are immutable and always ready for regulators.
Security Tooling Integration
Outstaffed Python devs extend SIEM connectors, build custom Splunk apps, and integrate threat-intel feeds, giving security teams a unified view of on-chain and off-chain events.
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