Job description

WHY SOCURE? Socure is building the identity trust infrastructure for the digital economy — verifying 100% of good identities in real time and stopping fraud before it starts. The mission is big, the problems are complex, and the impact is felt by businesses, governments, and millions of people every day. We hire people who want that level of responsibility. People who move fast, think critically, act like owners, and care deeply about solving customer problems with precision. If you want predictability or narrow scope, this won’t be your place. If you want to help build the future of identity with a team that holds a high bar for itself — keep reading. Data Scientist, Client Analysis (DS-II) About the role: We are currently looking for a Data Scientist (DS-II) to join our Data Science, Client Analysis team to be based remotely in the USA. In this unique role as Data Scientist, you will leverage your experience developing algorithms and analyzing massive data sets to tell compelling data stories while also working in partnership with the go-to-market team to drive revenue generation for Socure by ensuring that potential and existing customers can understand - through deep analysis - the benefit and value of Socure’s products throughout the pre and post sales cycle. This is an excellent opportunity for a Data Scientist who thrives when they're able to communicate a data story to an audience (tech and non-tech), and who is not satisfied only working behind the scenes. Data Scientists on the Client Analysis team are compensated for their part in driving new business with a generous incentive bonus opportunity on top of competitive base salary. 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. Follow Us! YouTube youtube.com | LinkedIn linkedin.com | X (Twitter) x.com | Facebook facebook.com

Requirements

Must-haves

Data Scientist, Client Analysis (DS-II)
We are currently looking for a Data Scientist (DS-II) to join our Data Science, Client Analysis team to be based remotely in the USA.
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
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

Nice-to-haves

You have a degree in a quantitative field, or equivalent work experience - advanced degree is preferred.
You have experience in identity verification and fraud prevention (strongly preferred)

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

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Platform: ashby
Effort: quick