Data Scientist II, Client Analysis

Summary

Socure is building identity trust infrastructure for the digital economy by verifying identities and preventing fraud. The Data Scientist II, Client Analysis role analyzes large customer datasets, develops algorithms and machine learning models, and creates compelling data stories to demonstrate product value. The role partners with go-to-market teams to support customer risk management, revenue generation, upsell opportunities, and product optimization.

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

Skills

• • 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
• • 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
• • You have experience in identity verification and fraud prevention (strongly preferred)
• Advanced degree is preferred

Qualifications

Must Haves

• • 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
• • 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

Nice to Haves

• • You have experience in identity verification and fraud prevention (strongly preferred)
• advanced degree is preferred

Benefits

• Remote work arrangement in the USA
• A generous incentive bonus opportunity on top of competitive base salary