Data Scientist ( For our FinTech Client)

Data Analytics team is seeking a talented and motivated Data Scientist to join our team. As a Data Scientist, you will play a crucial role in modelling complex problems, uncovering insights, and identifying new opportunities through the use of statistical, algorithmic, mining, and visualization techniques. You will be focused on utilizing our product data and analytics to solve business problems by applying machine learning and deep learning techniques, conducting statistical analysis, and building high-quality predictive systems that are integrated with our services.

Key Responsibilities:

• Interact with cross-functional teams to foster a data-driven payments organization.
• Develop data pipelines for models, including data preparation, cleaning, and transformations using open-source tools such as DBT, Feast, Kubeflow, and ML Flow.
• Work on big data systems such as Hive, Trino, and Spark for feature generation and data processing.
• Build data streaming applications and REST services for model serving in production.
• Compile complex predictive model packages for production deployment, support model installations, and monitor and calibrate production models.
• Analyze various data sources to generate reports and insights, both at the aggregate and model level, and present these results to a non-technical audience.
• Identify opportunities to create and automate repeatable analyses or build self-service tools for business users.
• Develop deep learning & Machine learning models to assist use cases in the payments domain.
• Design experiments, test hypotheses, and build, train, and deploy various models using traditional datasets and graph data.

Qualifications:

• Bachelor's degree in computer science or equivalent with 2+ years of experience in Data Science Domain
• Strong understanding of data science concepts, data structures, algorithms, and databases.
• Fluency in SQL and proficiency in programming in Python.
• Proficiency in machine learning and deep neural networks.
• Knowledge of visualization tools such as Tableau/Superset.
• Familiarity with basic principles of distributed computing and distributed databases.
• Good knowledge of data transformation techniques, Hypothesis Testing and statistical methodologies for insight generation.
• Strong communication skills and the ability to simplify complex information and results into simple concepts and actionable insights for a variety of audiences.