VAYUZ Technologies - Senior Data Analyst

Senior Data Analyst

Summary of Responsibilities:

- Candidate is expected to collaborate with other data scientists/Analyst, subject matter experts to deliver strategic analytics projects from design to execution.

- Identifying, analyzing, and interpreting trends or patterns in complex data sets.

- Providing expertise in data storage structures, data mining, and data cleansing.

- Translating numbers and facts to inform strategic business decisions.

- Create impactful presentations for stakeholder consumption summarizing analytical findings.

- Help identify emerging trends and conduct deep dive analysis to propose appropriate strategy.

- Develop and implement ML/predictive model for fraud detection.

- Conduct Complex analysis using statistical and other industry leading quantitative techniques.

- Conduct regular evaluation of fraud strategies that are implemented from both an operational and financial prospective.

Real-time Monitoring:

- Implement real-time monitoring systems to detect fraud as soon as it occurs.

- Utilize streaming analytics platforms for continuous data processing and immediate alerting.

Behavioral Analysis:

- Analyze user behavior and transaction patterns to identify deviations from normal behavior.

- Use clustering techniques to group similar behaviors and detect anomalies within each cluster.

Fraud Rules and Scoring:

- Develop fraud rules based on domain knowledge and historical fraud cases.

- Assign scores to transactions or activities based on their likelihood of being fraudulent.

Collaborative Filtering:

- Leverage collaborative filtering techniques to detect coordinated fraud schemes involving multiple entities or accounts.

Continuous Improvement:

- Regularly update models with new data and retrain them to adapt to evolving fraud patterns.

- Conduct periodic reviews of model performance and refine strategies based on feedback and insights.

Compliance and Ethics:

- Ensure compliance with regulatory requirements and ethical standards in handling sensitive data and making decisions affecting individuals.

- Implementing effective fraud analytics requires a combination of advanced analytics techniques, domain expertise, and a robust framework for data management and model deployment.

- Regular monitoring and adaptation to changing fraud tactics are essential to stay ahead of fraudulent activities.

Desired Skills and Experience:

- Experience of 4-10 years in R, Python, PL/SQL (Preferably MS SQL Server).

- Experience in BFSI domain, Indian Banks and NBFCs is a huge advantage.

- Understanding of Credit Bureau data is advantage.

- Proficiency in statistics and other tools/languages R, Python, SAS.

- Familiarity with relational databases and intermediate level knowledge of SQL.

- Ability to synthesize unstructured data and find actionable themes/insights using SAS/Python/R.

- Experience in Google Cloud Platform is a huge advantage.

- Strong problem solving skills.

- Ability to connect business requirements to data-mining objectives and business benefit.

- Demonstrated ability in gathering requirements, designs, plans and estimates.

- Aptitude to learn and ability to think creatively to solve real world business problems.

- Knowledge in at least one of the following Logistic regression models, Linear regression models, Stochastic models, Bayesian Modeling, Classification Models, Cluster Analysis, Neural Network, Non-parametric Methods, Multivariate Statistics will be additional advantage.