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# Entry-Level Data Scientist

- **Company:** Datavisor, Inc.
- **Location:** United States
- **Experience:** Starter
- **Contract:** Internship / Graduate position
- **Skills:** Artificial Intelligence, Amazon Web Services, Data Analysis, Microsoft Azure, Big Data, Cloud Computing, Computer Programming, Fraud Prevention and Detection, Apache Hadoop, Python (Programming Language), Machine Learning, NumPy, Tensorflow, SQL Databases, Transaction Data, Data Processing, Google Cloud, Pytorch, Apache Spark, Pandas, Scikit Learn, Information Technology, Dask, Data Management, Unsupervised Learning
- **Published:** September 4, 2026
- **Apply:** https://startup.jobs/data-scientist-fraud-detection-datavisor-6785838

## About the Role

* Master's degree in Computer Science, Data Science, Statistics, or a related quantitative field. Ph.D. degree is a plus.
 * Strong programming skills in Python and familiarity with data science libraries (NumPy, Pandas, scikit-learn, TensorFlow/PyTorch 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 problem-solving skills and patience for deep-dive data exploration.
 * Prior internship or project experience in fraud modeling, risk analysis, or related fields is a plus.
 * Excellent communication skills and ability to work in a collaborative environment.

Nice to have

 * Familiarity with big data tools (Spark, Hadoop, Dask).
 * Knowledge of graph-based fraud detection techniques.
 * Experience with cloud platforms (AWS, GCP, Azure).

## Description

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.


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