Lead Data Scientist

Summary

Join Tide as a Lead Data Scientist and build intelligence into products to significantly reduce fraud and improve FinCrime efforts. Collaborate with the FinCrime team to solve business challenges, design data products, and leverage machine learning for fraud detection. You will build and optimize models, productionize them, adopt new methodologies, and coach junior data scientists. The role requires extensive experience in machine learning, large-scale data handling, and deploying models in production. Tide offers a competitive salary, flexible working arrangements, and various benefits including health insurance, life insurance, learning and development budget, and paid time off.

Requirements

• 8+ years of experience as a Data Scientist, with a proven track record in solving complex problems, particularly in fraud detection or financial crime
• Extensive experience in designing, developing, and deploying machine learning models to detect and mitigate fraud. You should be comfortable translating business challenges into data-driven solutions
• Proficiency in handling large, tabular datasets, and applying robust techniques for data analysis and model training
• Experience with tools such as PySpark, Databricks, AWS, or GCP for processing large datasets, training models, and deploying them at scale
• Proven ability to deploy models into production environments, optimizing them for performance and scalability, while ensuring they remain effective over time
• Expertise in monitoring and maintaining the health and performance of models post-deployment to ensure continuous improvement and fraud detection accuracy
• Background in the Fintech industry, with specific experience in financial crime and fraud detection, applying data science to solve real-world business problems
• Strong interpersonal skills to collaborate effectively with data engineers, machine learning engineers, and product managers in an agile, iterative environment. Ability to communicate complex insights clearly to both technical and non-technical stakeholders

Responsibilities

• Collaborate with the FinCrime team to identify and solve fraud detection problems, using data science to drive business decisions and significantly reduce fraudulent activities
• Translate business requirements into data products and models that address specific fraud detection challenges
• Train machine learning models, optimize hyperparameters, design KPIs, and implement experiments to improve fraud detection accuracy and business outcomes
• Work with machine learning engineers and data engineers to deploy models into production, ensuring they are scalable and optimized for real-time fraud detection
• Lead the adoption of innovative methods and technologies, continuously improving fraud detection models and data science practices
• Mentor and guide junior team members, setting best practices for model development, optimization, and deployment
• Serve as a subject matter expert, providing guidance on complex technical concepts related to fraud detection, machine learning, and data science

Benefits

• Competitive salary
• Self & Family Health Insurance
• Term & Life Insurance
• OPD Benefits
• Mental wellbeing through Plumm
• Learning & Development Budget
• WFH Setup allowance
• 15 days of Privilege leaves
• 12 days of Casual leaves
• 12 days of Sick leaves
• 3 paid days off for volunteering or L&D activities
• Stock Options
• Make work, work for you! We are embracing new ways of working and support flexible working arrangements. With our Working Out of Office (WOO) policy our colleagues can work remotely from home or anywhere in their assigned Indian state. Additionally, you can work from a different country or Indian state for 90 days of the year