Head – Data Science and GenAI

1 week ago

Mumbai, Maharashtra, India HDFC securities Full time

Leadership and Strategy:

  • Develop and execute a comprehensive data science and Gen AI strategy for various functions such as trading strategies, risk management, customer segmentation, etc.
  • Implement innovative data-driven solutions to improve decision-making processes across the organization resulting in improvement in efficiency and reduction in operational costs.
  • Provide visionary leadership to the data science and AI teams, fostering a culture of innovation and collaboration.
Model Development and Validation for trading strategies optimization and predictive market analysis:

  • Lead the development of predictive models for various applications like customer churn prediction, fraud detection, algorithmic trading models, etc. Implement machine learning models for pattern recognition, trend analysis, and risk assessment to enhance trading decision-making.
  • Ensure the robustness and accuracy of models through rigorous validation processes.
  • Develop AI-powered algorithms to optimize trading strategies based on historical market data, real-time market conditions, and predictive analytics.
  • Utilize AI techniques such as predictive modeling and sentiment analysis to forecast market trends, stock price movements, and volatility.
  • Generate actionable insights for traders and investors to make informed decisions on buying, selling, or holding stocks.

Data Governance and Management:

  • Establish and enforce data governance policies to ensure the quality, security, and integrity of financial data.
  • Collaborate with cross-functional teams to optimize data collection, storage, and retrieval processes.
  • Improve data accuracy, reduce data security incidents, and streamline data retrieval processes resulting in reduction in turnaround time.

Customer Engagement and Retention:

  • Increase in customer engagement metrics (e.g., average time spent on platform, frequency of trades) driven by personalized recommendations and targeted marketing campaigns.
  • Improvement in customer retention rates and decrease in churn rate among high-value customers.
  • Reduction in the time and resources required to develop and deploy new data science solutions.
  • Increase in automation levels across data processing, model training, and deployment processes.
  • Utilize AI techniques for customer segmentation based on demographics, behavior, and investment preferences. Implement personalized marketing campaigns and investment recommendations tailored to the needs and preferences of different customer segments.

Research and Innovation:

  • Stay abreast of the latest developments and trends in data science, machine learning, and financial markets.
  • Foster a culture of innovation by encouraging experimentation and exploration of new techniques and technologies.
  • Conduct market research and competitive analysis to identify market trends, customer preferences, and emerging opportunities for GenAI applications.
  • Stay abreast of industry developments and competitor strategies in AI-driven trading and investment solutions.

Advanced Analytics and Machine Learning:

  • Drive the development and implementation of advanced analytics models and machine learning algorithms to extract valuable insights.
  • Ensure the application of cutting-edge technologies to solve complex business problems.
  • Deliver actionable insights leading to improvement in key business metrics

Risk Management and Compliance:

  • Develop risk management models and tools to identify, assess, and mitigate various types of risks, including market risks, credit risks, and operational risks.
  • Ensure compliance with regulatory requirements and industry standards related to data privacy, security, and financial regulations.

Operational Efficiency and Automation:

  • Implement data-driven automation solutions to streamline operational processes, reduce manual effort, and enhance efficiency.
  • Identify opportunities for process optimization and cost reduction through data analytics and automation initiatives

Gen AI Integration:

  • Spearhead initiatives to integrate General Artificial Intelligence (Gen AI) into various business processes for enhanced efficiency and innovation.
  • Promote the adoption of GenAI across the organization, inspiring all teams to integrate and enhance their operational efficiency through its utilization.
  • Collaborate with technology teams to implement AI solutions that align with organizational goals, resulting in improvement in operational efficiency and increase in customer satisfaction.

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