Senior Data Scientist
Talkiatry
Amazon RedshiftBigQueryPandasPythonScikit-LearnSQL
Data Scientist, Watchlist
Socure
full-time
Posted on:
Location Type: Remote
Location: Remote • 🇺🇸 United States
Visit company websiteSalary
💰 $110,000 - $130,000 per year
Job Level
Mid-LevelSenior
Tech Stack
AWSHadoopPythonPyTorchScikit-LearnSparkSQLTensorflow
About the role
- Design, develop, and implement machine learning models and statistical algorithms to support the development of fraud detection and identity verification solutions, leveraging large-scale and diverse data sources.
- Analyze large datasets and uncover actionable insights, fraud patterns, and new opportunities for product and service enhancements across Socure’s platform.
- Collaborate with product, engineering, and cross-functional teams to translate business requirements into data-driven solutions that align with company goals.
- Develop and code data processing pipelines, automated workflows, and tools to cleanse, integrate, and evaluate data from multiple sources.
- Provide analytical support to the fraud and risk data science team; present findings and communicate data-driven insights with clear storytelling tailored to technical and non-technical audiences.
- Continuously test and apply the latest machine learning algorithms, libraries, and techniques to improve model performance and adaptability.
- Build, maintain, and monitor robust, scalable models deployed into production environments; participate actively in code reviews and peer discussions.
- Contribute to a collaborative, high-performance team environment; seek out and communicate trends, patterns, or anomalies that inform Socure’s broader product strategies.
Requirements
- Bachelor’s degree in Computer Science, Mathematics, Statistics, or a related quantitative field, or equivalent professional experience.
- Proficiency in Python (preferred) or R, with hands-on experience in machine learning libraries such as scikit-learn, TensorFlow, PyTorch, or XGBoost.
- Demonstrated ability to analyze, clean, and model large-scale datasets using SQL and modern data tools (e.g., AWS, Databricks, Hadoop/Spark).
- Working knowledge of supervised and unsupervised learning, feature engineering, and model evaluation approaches.
- Experience translating business challenges into data science solutions and clearly communicating outcomes.
Benefits
- Offers Equity
- Offers Bonus
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard skills
machine learningstatistical algorithmsdata processing pipelinesdata analysisfeature engineeringmodel evaluationPythonRSQLlarge-scale datasets
Soft skills
collaborationcommunicationanalytical supportstorytellingproblem-solvingteamworkadaptabilityinsight generationtrend analysispresentation skills
