D
DataVisor
Data Scientist (Fraud Detection)
Skills
Google Cloud PlatformSQL QueriesBig DataPythonData ScienceNumPypandasPyTorchTensorFlowData AnalysisMachine LearningAIAWSHadoopAzure
2 months ago
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Important information
Contract type:
Permanent
Location:
Mountain View, CA, USA
Work mode:
Onsite
Published on:
29 August 2026
What they need
- We are looking for a motivated Entry-Level Data Scientist to join our Fraud Detection team
- In this role, you will leverage your machine learning and data analysis skills to identify fraudulent activities, build predictive models, and uncover hidden patterns in large datasets
- You will work closely with cross-functional teams to develop scalable solutions that enhance our fraud detection capabilities
- This is a great opportunity to grow your skills in a fast-paced, data-driven environment while making a real impact in the fight against fraud
- Develop and deploy machine learning models for fraud detection and risk assessment
- Perform exploratory data analysis (EDA) to identify trends, anomalies, and patterns in transactional data
- Clean, preprocess, and analyze large datasets using Python and popular data science libraries (pandas, NumPy, scikit-learn, etc.)
- Collaborate with engineering and business teams to integrate ML models into production systems
- Continuously monitor model performance and refine algorithms to improve accuracy
- Stay updated with the latest advancements in fraud detection techniques and ML/AI technologies
Benefits
- Stock Options
- Commuter Passes
- Paid Time Off
- Catered Lunch and Dinner
- Team and Company Outings- Prior internship or project experience in fraud modeling, risk analysis, or related fields is a plus
- Strong problem-solving skills and patience for deep-dive data exploration
- Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, or a related quantitative field. Ph.D. degree is a plus
- Solid understanding of machine learning algorithms (supervised/unsupervised learning, anomaly detection, classification, etc.)
- Experience with SQL and data manipulation/analysis in large datasets
- Strong programming skills in Python and familiarity with data science libraries (NumPy, Pandas, scikit-learn, TensorFlow/PyTorch is a plus)
- Excellent communication skills and ability to work in a collaborative
- Knowledge of graph-based fraud detection techniques
- Experience with cloud platforms (AWS, GCP, Azure)
- Familiarity with big data tools (Spark, Hadoop, Dask)
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