Senior Data Analyst

4 days ago

Aurangabad, Maharashtra, India beBeeFraud Full time ₹ 1,80,00,000 - ₹ 2,40,00,000
Fraud Data Analyst

We are seeking a seasoned Fraud Data Analyst to join our team.

  1. Develop and deploy predictive analytics models and machine learning algorithms to identify suspicious activities and patterns. Develop a comprehensive understanding of fraud tactics and techniques.
  2. Continuously optimize fraud monitoring systems to improve detection accuracy and reduce false positives. Stay up-to-date with emerging fraud trends and industry benchmarks.
  3. Analyze internal and external data sources to identify vulnerabilities and recommend proactive measures. Develop a data-driven approach to risk management.
  4. Define and track key performance indicators (KPIs) to measure the effectiveness of fraud detection strategies. Provide actionable insights to inform strategic decision-making.
Market Intelligence
  1. Stay updated on emerging fraud tactics, industry benchmarks, and regulatory changes. Develop a deep understanding of market trends and competitor analysis.
  2. Analyze competitors' risk management strategies to identify opportunities for improvement. Identify areas for growth and development.
  3. Provide actionable insights from market intelligence to inform strategic decision-making. Drive business growth through data-driven decisions.
Team Leadership
  1. Recruit, develop, and mentor a high-performing team of data analysts, data scientists, and market intelligence specialists. Foster a culture of innovation and collaboration.
  2. Work closely with risk management, compliance, IT, and other departments to ensure alignment and effective communication. Build strong relationships with stakeholders.
Qualifications

Education: Master's degree in data science, statistics, economics, business administration, or a related field.

Experience: 10+ years of experience in fraud analytics, risk management, or data analytics. Proven track record of developing and implementing fraud detection systems.

Technical Skills: Expertise in data analytics tools (e.g., Python, R, SQL, SAS). Familiarity with machine learning platforms and fraud detection software.

Key Competencies: Strong analytical and problem-solving skills. Excellent leadership and team-building abilities. Strategic thinker with strong business acumen.

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