Description : Role Overview :
We are seeking a highly skilled Data Scientist to join our team and work on developing secure, scalable data pipelines, building robust data models, and deploying machine learning models for biometric and security applications.
You will collaborate with cross-functional teams to process large-scale security datasets and extract meaningful insights to improve fraud detection, authentication systems, and risk assessment.
Key Responsibilities :
Data Pipeline Development :
- Design and build scalable data pipelines to process, clean, and transform large security and biometric datasets.
- Optimize data ingestion, storage, and retrieval for real-time and batch processing.
Data Modeling & Machine Learning :
Develop and implement predictive models for biometric authentication, fraud detection, and anomaly detection.Train, evaluate, and optimize machine learning models (e.g., CNNs for facial recognition, anomaly detection algorithms for fraud prevention).Work with deep learning frameworks (TensorFlow, PyTorch) for advanced securityapplications.
ETL & Data Processing :
Design and manage ETL workflows to extract, transform, and load data from multiple sources.Ensure data integrity, consistency, and security compliance in ETL processes.Work with structured & unstructured data from biometric sensors, access logs, and cybersecurity sources.Security & Compliance :
Implement best practices for data security, encryption, and access control in ML models.Collaborate with security engineers to detect and mitigate data-related threats.Required Skills & Qualifications :
Education & Experience :
Bachelor's / Masters degree in Computer Science, Data Science, AI, or a related field.3+ years of experience in data science, machine learning, or data engineering, preferably in a security or biometrics-focused company.Technical Skills :
Proficiency in Python, SQL, Spark, and cloud platforms (AWS, GCP, or Azure).Experience with ML frameworks (TensorFlow, PyTorch, Scikit-Learn).Strong knowledge of ETL, data pipelines, and workflow orchestration tools (Airflow, Kafka,etc.).
Familiarity with biometric technologies (face recognition, fingerprint analysis, behavioralbiometrics) is a plus
(ref : hirist.tech)