Responsibilities
Analyze massive customer data sets, come up with actionable insights, and explain how our models perform and how we can help our customers build optimal risk management policies
Act as a Data Science advocate: deeply understand Socure’s solutions (products, models and algorithms) and customers’ risk challenges to educate and influence from a scientific perspective
Create convincing data stories to showcase how we can help our customers eliminate identity fraud, streamline their end-user experience, and support their risk management efforts holistically
Provide thought leadership and be the customer’s voice for building the next generation of Socure’s core models and product
Create tools and automated workflows to improve the speed, accuracy, and reproducibility of our analysis
Partner closely with GTM teams (Sales, Solution Consultants, Account Managers and Technical Account Managers) to derive creative ways of analysis and identify opportunities for upsell and product optimization
Build ML models when it is advantageous to explore different approaches over the established models in production
Qualifications
You have a degree in a quantitative field, or equivalent work experience - advanced degree is preferred.
You have 2+ years experience in data science, data analysis, or analytics engineering
You have extensive theoretical and practical understanding of state-of-the-art supervised and unsupervised machine learning methods
You know how to write clean, performant code in Python, and have 2+ years experience working with massive real-life datasets
You have experience querying relational databases with SQL
You have experience working with cloud tools and technologies in AWS, Azure, Databricks, or GCP
You know how to tell compelling stories with data (dashboarding, building interactive data stories and actionable presentations)
You are able to explain very complex algorithms such as ML/AI models, and analyses to non-technical audiences
You are an excellent verbal and written communicator and are comfortable delivering presentations with clear, complete messages
You thrive in a remote startup work environment and are excellent at setting clear goals and holding yourself accountable
You have experience in identity verification and fraud prevention (strongly preferred)
TECHNOLOGIES WE USE
The Data Science Client analysis team works across customer data, fraud and identity analytics, model evaluation optimizing workflows, monitoring/alerts, reporting and more. An ideal candidate will have experience with several of the technologies below and be excited to learn the rest.
Python ecosystem: PySpark, Pandas, NumPy, H2O, SHAP, Seaborn, Jupyter, and related data-science libraries
SQL and data warehouses: SQL, Redshift, Snowflake, and S3
Data processing: Databricks, Apache Spark, Apache Arrow, and Amazon EMR
Data pipelines and automation: Airflow, batch processing, SFTP/PGP, webhook data, and automated daily/weekly reporting
Model evaluation and risk analytics: backtesting, train/holdout/OOT analysis, performance monitoring, threshold tuning, and model/rule QA
Visualization and storytelling: Tableau, Looker, dashboards, and interactive presentations
ML/AI workflows: supervised and unsupervised learning, transformers, clustering, graph analytics, explainability, and LLM/agentic workflows
Engineering and analytical practices: Git-based version control, production-quality and reproducible analysis, automated data-quality and validation testing, API integrations, and working with structured data formats such as JSON.
- Socure is an equal opportunity employer that values diversity in all its forms within our company. We do not discriminate based on race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
- If you need an accommodation during any stage of the application or hiring process—including interview or onboarding support—please reach out to your Socure recruiting partner directly.
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