Selected Intern's Day-to-day Responsibilities Include
- Assist in designing, developing, and testing AI/ML models for banking, collections, recovery, and financial analytics use cases.
- Work on data preprocessing, cleaning, feature engineering, and dataset preparation from structured and unstructured financial data.
- Support development of predictive models for collections, default prediction, customer segmentation, and risk scoring.
- Help build and optimize Generative AI and LLM-based workflows for automation, customer communication, and analytics.
- Participate in training, validation, fine-tuning, and performance evaluation of AI models.
- Collaborate with the product and engineering teams to integrate AI models into production systems and APIs.
- Conduct research on the latest AI/ML techniques, frameworks, and fintech AI innovations.
- Assist in creating dashboards, reports, and visualizations for model outputs and business insights.
- Monitor model accuracy, drift, and performance, and suggest improvements.
- Write clean, scalable, and well-documented Python code for AI/ML pipelines.
- Support deployment activities using cloud platforms and MLOps tools where required.
- Participate in internal brainstorming sessions and contribute innovative AI-driven ideas for product enhancement.
- Maintain confidentiality and security of sensitive financial and customer data while working on AI systems.
- Prepare technical documentation, experiment summaries, and model performance reports for internal review.
About Company: Markytics is a team of highly qualified and passionate data science/ML professionals. At Markytics, our objective is to develop strategic partnerships with our clients and deliver improved profits and enhanced customer value by drawing on our strengths in data analytics and statistical modeling. We are a global analytics and insights provider firm that helps companies understand how and why their customers make decisions. We help companies to understand customer expectations, improve customer experience, and secure customer management. We strive to make data science accessible to and usable by everyone across small, medium, and large-scale enterprises.
