Data Science Engineer
Data Science Engineer
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Job Description
We are seeking a skilled and driven Data Science Engineer to join our team focused on developing and deploying advanced fraud detection models for credit card transactions. This role will play a critical part in identifying fraudulent behavior in realtime leveraging cuttingedge data science techniques and tools within the Azure ecosystem and Databricks environment.
Key Responsibilities:
Design develop and deploy machine learning models to detect fraudulent credit card transactions.
Analyze large volumes of structured and unstructured data to uncover patterns trends and anomalies related to fraud.
Build scalable data pipelines and model training workflows using Databricks on Azure.
Work closely with data engineering and platform teams to productionalize models and monitor performance.
Continuously evaluate and refine models to improve accuracy precision and recall over time.
Collaborate with crossfunctional teams including fraud operations engineering and compliance.
Required Qualifications:
7 years of experience in data science or machine learning engineering roles.
Proven experience developing fraud detection models or working with financial transaction data.
Strong programming skills in Python and SQL.
Experience with Databricks Spark and Azure ML or related Azure data services.
Solid understanding of machine learning techniques including supervised/unsupervised learning anomaly detection and model evaluation.
Excellent analytical and problemsolving skills with a strong attention to detail.
Preferred Qualifications:
Experience in the payments or financial services industry is a BIG plus.
Experience in Microsoft Fabric is a plus.
Familiarity with realtime data processing and stream analytics.
Knowledge of model monitoring drift detection and model retraining strategies.
Microsoft Fabric,Azure Data Bricks, Machine Learning, Data scientist
Employment Type
Full Time
