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Socure

Data Scientist II, Client Analysis

Socure is hiring a Data Scientist II, Client Analysis for a remote role open to applicants in United States. It pays $150k-$185k a year and Level rates it ; you can apply on Socure.

Level's read on this job

  • On Level's scale, this data scientist role is Works on AI ●●●○: the daily work is on AI products, without building the model.
  • The posting lists this role as remote.
  • Tools and skills the posting cites include Databricks, AI agents and AI evaluation.
  • Level classifies it as a mid-level role.
  • Level lists 85 other open roles at Socure.

AI in this role

Analyze massive customer datasets and communicate identity model performance to drive revenue and client success.

databricks
ai-agentsai-evaluationdata-scienceclient-analysisalgorithm-developmentrisk-managementpython

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.



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How we rate this

Data Scientist II, Client Analysis at Socure rates 60 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.

Classification

Works on AI. The daily work is on AI products, without building the model.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

AI agentsAI EvaluationData ScienceClient AnalysisAlgorithm DevelopmentRisk ManagementPythonDatabricks

Also common in data scientist jobs at this level

Pay

This job starts at
$150k
Typical data scientist job
$166k

This posting starts 10% below the typical data scientist job. See data scientist jobs

Questions you could be asked

  1. How do you decide when an AI agent can act on its own versus asking for approval first?
  2. How do you decide that one model's output is better than another's for a given task?
  3. Tell me about a project where data science was part of your work. What did you do?
  4. Tell me about a project where client analysis was part of your work. What did you do?
  5. Tell me about a project where algorithm development was part of your work. What did you do?

Adapt your resume

  • List these exact terms on your resume: AI agents, AI Evaluation, Data Science, Client Analysis, and Algorithm Development. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
  • Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.

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