Location: Bangalore ,None,None

Position OverviewJob Title: Data ScientistDepartment: ServicesReporting To: Service Delivery Head, IndiaTookitaki is seeking a Data Scientist to join our high-performing Data Science Team, focused on building AI-powered solutions for real-time fraud detection and AML (Anti-Money Laundering) compliance. As a Data Scientist at Tookitaki, you will be instrumental in solving complex data problems, developing predictive analytics and anomaly detection models, and enhancing the performance of our FinCense and AFC Ecosystem platforms. This role requires strong analytical, machine learning, and data engineering skills, along with excellent communication abilities for client interactions. Position PurposeThe purpose of this role is to design, develop, and deploy advanced machine learning models that enhance Tookitaki’s ability to detect financial crimes, mitigate risks, and improve compliance efficiency for global banks and fintech clients. The Data Scientist will work closely with cross-functional teams, including Engineering, Product, and Client Success, to deliver high-accuracy predictive models, improve anomaly detection, and operationalize AI at scale. This role directly contributes to Tookitaki’s mission of creating a safer and more trustworthy financial ecosystem.Key ResponsibilitiesProblem Comprehension & Solution DesignUnderstand client business problems, defining the prediction objectives, and identifying value creation opportunities for clients.Ask first-principle questions to approach problem-solving with clarity and precision.Data Analysis & Feature EngineeringAnalyze large, complex, multi-dimensional datasets from multiple sources and create relevant features for machine learning models.Translate data access, transformation, and movement requirements into functional and scalable data pipelines.Model Development & EvaluationDesign, develop, and optimize predictive models for anomaly detection and risk modeling.Apply advanced approaches like ensemble methods, stacking, and model blending to improve model accuracy and robustness.Evaluate algorithm performance and fine-tune models to achieve high precision and recall rates.Algorithm Understanding & ApplicationDemonstrate a deep understanding of machine learning algorithms, their mathematical foundations, and the appropriate use cases for each.Innovate and deploy custom algorithms tailored to fraud and AML use cases within Tookitaki’s AFC Ecosystem and FinCense platforms.Client Communication & Stakeholder ManagementPresent complex models and analyses to clients and internal stakeholders in a clear and precise manner.Manage client expectations, ensure on-time delivery, and translate client feedback into model improvements.Documentation, Collaboration & Knowledge SharingMaintain comprehensive documentation of models, workflows, and processes.Collaborate with cross-functional teams, ensuring seamless integration of data science models into production.Contribute to training sessions, workshops, and continuous learning initiatives within the team.Qualifications and SkillsEducationBachelor’s or Master’s degree in Computer Science, Data Science, Mathematics, Statistics, or related fields.Experience3–5 years of experience in predictive analytics, machine learning, or forecasting.Prior experience in transactional anomaly prediction or operational risk modeling is highly desirable.Technical ExpertiseProficiency in Python, with the ability to write production-ready code.Familiarity with Scala is a plus.Hands-on experience with big data frameworks like Spark and Hadoop is preferred.Proficiency in SQL and experience working with relational and non-relational databases.Understanding of ETL processes, data flow modeling, and pipeline development.Soft SkillsStrong communication skills, both written and verbal, especially in client-facing roles.Team player with the ability to collaborate in a cross-functional and fast-paced environment.Passionate about working in startup environments and solving complex data challenges.Key CompetenciesMachine Learning & Predictive Modeling: Deep understanding of ML algorithms, model development, and optimization techniques.Analytical & Problem-Solving Skills: Ability to analyze complex datasets, apply first-principle thinking, and develop innovative solutions.Communication & Client Engagement: Proven ability to communicate technical insights to non-technical stakeholders and manage client expectations.Collaboration & Teamwork: Works effectively with cross-functional teams, including Engineering, Product, and Client Success.Continuous Learning & Innovation: Strong desire to learn new tools, participate in competitions (e.g., Kaggle), and push the boundaries of AI applications in financial crime prevention.Success MetricsSuccessful deployment of high-accuracy models that improve detection rates and reduce false positives in AML and fraud use cases.On-time delivery of projects and solutions that meet or exceed client expectations.Improvement in model performance metrics (precision, recall, F1-score) by X% over baseline models.Client satisfaction scores and positive feedback on solution implementation and impact.Contribution to team learning and innovation, including participation in competitions and internal training initiatives.BenefitsCompetitive compensation, including attractive variable pay components.Flexible working hours, with a focus on results and outcomes.Opportunity to build AI and analytics products for global financial markets.Learning and growth opportunities, with exposure to advanced AI and machine learning applications in the RegTech space.Work with an award-winning, industry-recognized company in artificial intelligence and advanced machine learning.Opportunity to collaborate with some of the world’s leading banks and fintech firms, delivering solutions that redefine financial crime prevention.
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