01Key Responsibilities
Develop and implement predictive models and machine learning algorithms to detect fraudulent transactions and suspicious activities.
Analyze large, complex datasets from multiple sources to identify patterns and trends related to AML compliance and financial risk.
Collaborate with risk and compliance teams to define data requirements, risk indicators, and reporting metrics.
Design and maintain dashboards and automated reports to monitor risk exposures and AML KPIs.
Conduct ad-hoc analyses to support regulatory audits, investigations, and risk assessments.
Ensure that all data analyses comply with legal, regulatory, and internal policies.
Continuously improve data collection, preprocessing, and modeling techniques for higher accuracy and efficiency.
Stay updated on industry best practices, emerging risks, and advanced analytics methods in AML and financial crime detection.
Required Skills and Qualifications:Bachelors or Masters degree in Data Science, Statistics, Computer Science, Mathematics, Finance, or a related field.
Strong proficiency in programming languages such as Python, R, or SQL.
Experience with machine learning frameworks (e.g., scikit-learn, TensorFlow, PyTorch) and statistical modeling.
Solid understanding of AML regulations, financial crimes, risk management, and compliance processes.
Expertise in data visualization tools such as Tableau, Power BI, or similar platforms.
Knowledge of big data technologies (Hadoop, Spark) is a plus.
Strong analytical thinking, problem-solving, and critical reasoning skills.
Excellent written and verbal communication skills to convey complex findings to non-technical stakeholders.
Experience:35 years of experience in data science, risk analytics, fraud detection, or AML compliance within the financial or fintech industry.
Proven track record in designing and deploying predictive models for risk mitigation.
Hands-on experience with regulatory reporting, compliance monitoring, or financial crime investigations.
Working Hours:Full-time role (MondayFriday, 40 hours per week).
Flexibility in remote/hybrid working arrangements depending on project requirements.
Knowledge, Skills, and Abilities:Ability to work with large datasets and extract actionable insights.
Strong statistical and quantitative analysis capabilities.
Detail-oriented with a high degree of accuracy and integrity.
Capable of prioritizing multiple tasks and meeting tight deadlines.
Strong collaboration and teamwork skills in a fast-paced environment.
Continuous learner with the ability to adapt to new technologies and regulatory requirements.
Benefits:Competitive salary and performance-based incentives.
Health, dental, and vision insurance.
Flexible work arrangements (remote/hybrid options).
Professional development opportunities, including training in risk analytics and AML compliance.
Dynamic startup culture with exposure to cutting-edge fintech projects.
Paid time off, holidays, and wellness programs.
Why Join Startup Inno:At Startup Inno, you will be part of a forward-thinking team dedicated to redefining risk analytics and compliance in the financial technology space. You will have the opportunity to innovate, grow professionally, and make a direct impact on safeguarding the company and its clients from financial crimes. We value creativity, collaboration, and continuous learning, offering an environment where your insights truly matter.
How to Apply:Interested candidates are encouraged to submit their resume and a cover letter outlining relevant experience and achievements to us with the subject line: Application Data Scientist (Risk Analytics & AML Compliance).
Only shortlisted candidates will be contacted for further assessment. .
