Tookitaki Technologies - Data Scientist - SaaS Platform (6-10 yrs)

Position Overview :

Job Title : Application Engineer

Department : Services Delivery Team

Location : Cluster Focusses

Reporting To : Regional Head of Service Delivery

The Application Engineer will play a pivotal role in configuring Tookitaki's FinCense platform to meet client-specific requirements. This role requires a strong data science background, technical expertise in big data technologies, and exceptional problem-solving skills to ensure successful client deployments and ongoing system performance.

Position Purpose :

The Application Engineer is responsible for customizing the FinCense platform to address client-specific compliance and operational needs. Collaborating with Deployment Engineers, Data Engineers, and Client Enablement teams, the Application Engineer ensures seamless implementation, configuration, and ongoing performance optimization.

This role is critical to the successful deployment of Tookitaki's platform across both on-premise and cloud-hosted (CaaS) environments. It requires a deep understanding of data science workflows, the ability to translate business needs into technical configurations, and an analytical mindset to solve complex client challenges.

Key Responsibilities :

1. Product Configuration and Customization :

• Configure Tookitaki's FinCense platform based on client-specific requirements and workflows.
• Implement data science models, algorithms, and workflows tailored to client use cases.
• Collaborate with Client Enablement and Deployment Engineers to align configurations with best practices and ensure readiness for go-live.

• Assist in designing and optimizing data pipelines for real-time and batch processing.
• Configure and fine-tune algorithms for AML (Anti-Money Laundering) and fraud detection.
• Validate model performance and ensure alignment with compliance objectives.

• Collaborate with Data Engineers to integrate client data into the FinCense platform.
• Troubleshoot and resolve performance issues related to data ingestion, processing, and model execution.
• Leverage expertise in Big Data technologies (Hadoop, Spark, Hive, ElasticSearch) to optimize platform performance.

• Partner with the Client Enablement team to deliver training and documentation for end-users.
• Work closely with Product Management to provide feedback on product enhancements.
• Support Deployment Engineers in ensuring successful on-premise and cloud deployments.

• Maintain detailed documentation of configurations, workflows, and issue resolutions.
• Develop templates, FAQs, and troubleshooting guides to support the Services and Client Success teams.
• Identify and implement process improvements to enhance deployment efficiency and client satisfaction.

• Required: Bachelor's degree in Computer Science, Data Science, or related technical field.
• Preferred: Master's degree in Data Science, Artificial Intelligence, or Big Data Analytics.

• Minimum: 6 years of experience in configuring SaaS platforms or data-intensive systems.
• Proven track record in deploying or configuring platforms for banks, fintech, or regulated industries.

• Strong knowledge of Big Data frameworks : Hadoop, Spark, Hive, ElasticSearch, and Kubernetes.
• Proficiency in programming languages : Python, SQL, and familiarity with data manipulation libraries.
• Experience in model deployment : Optimizing ML/AI workflows and data pipelines for large-scale systems.
• Understanding of cloud infrastructure : AWS (preferred), GCP, or Azure.

• Excellent communication skills to explain technical solutions to non-technical stakeholders.
• Strong problem-solving skills with an analytical mindset.
• Ability to collaborate effectively in cross-functional teams.

• Experience with AML or fraud detection platforms is a strong plus.
• Certifications in AWS, Kubernetes, or Big Data frameworks are advantageous.

• Client-Centric Mindset: Ensures configurations align with client objectives.
• Technical Acumen: Strong grasp of Tookitaki's tech stack and ability to adapt to new technologies.
• Problem-Solving: Proactively addresses challenges and identifies root causes.
• Collaboration: Works effectively with diverse teams to deliver seamless solutions.