Data Scientist

3 weeks ago

Pune, Maharashtra, India Kaivale Technologies Full time

Role Summary :

We are seeking an experienced Data Scientist / AI Expert to lead the design, development, and deployment of intelligent systems that enhance fraud detection, transaction scoring, and customer insights within our payment platform.

You will leverage a mix of real-time and historical transactional data to build robust, scalable machine learning models that drive accuracy and efficiency while maintaining strict data privacy and compliance standards.

In this role, you will collaborate with data engineers, backend developers, product owners, and compliance teams to translate complex data into actionable insights and reliable AI-powered decision Responsibilities :

- Design, implement, and validate advanced machine learning models focused on fraud detection, anomaly detection, transaction scoring, and customer behavior analysis.

- Analyze large volumes of heterogeneous data, including transactional records, behavioral metrics, device fingerprints, and network data, to uncover patterns and develop predictive features.

- Build scalable data pipelines and automated feature engineering workflows that prepare clean, enriched datasets for ML training and inference.

- Work closely with backend engineers to integrate ML models into production microservices, ensuring real-time inference capabilities and system reliability.

- Continuously monitor model performance, retrain models as necessary, and optimize algorithms to adapt to evolving fraud patterns and business needs.

- Apply data masking, anonymization, and PCI-DSS-compliant data processing techniques to ensure the security and privacy of sensitive payment data.

- Develop and maintain interactive dashboards and reports for business stakeholders, compliance teams, and risk management, enabling data-driven decision-making.

- Stay updated with the latest advances in AI/ML, especially those applicable to fintech, fraud prevention, and real-time decisioning, and incorporate best practices and novel methods into our Skills & Qualifications :

- Experience : 3 to 5+ years of hands-on experience in data science, machine learning engineering, or applied AI roles.

- Strong proficiency in Python and data science libraries such as Pandas, Scikit-learn, TensorFlow, or PyTorch.

- Proven experience in building models for fraud detection, anomaly detection, unsupervised learning, and real-time inference systems.

- Familiarity with big data tools and workflow orchestration such as Apache Spark, Airflow, Kafka, and ClickHouse is a strong plus.

- Strong SQL skills with experience in PostgreSQL or other analytical/transactional databases.

- Prior experience in risk engines, credit scoring, payments, or financial fraud detection is highly preferred.

- Excellent problem-solving skills with the ability to handle noisy, incomplete, or biased datasets (ref:hirist.tech)

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