Data Scientist Ii Big Data Rd Identity Graph Kyc

Data Scientist II - Big Data R&D, Identity Graph & KYC at SentiLink — Research Report

Introduction

This report provides an insider-level guide to the Data Scientist II role at SentiLink, focusing on Big Data R&D, Identity Graph, and KYC (Know Your Customer). The position is currently open with a deadline noted as Reposted Yesterday, indicating active hiring urgency for remote or hybrid candidates in New York, NY. Securing this role offers a unique pathway into the fintech identity verification sector, where you will build systems that prevent fraud and enable secure digital onboarding for major financial institutions.

Overview of SentiLink

SentiLink is a leading fintech company specializing in identity verification and fraud prevention solutions. The company aggregates data from over 1,000 sources to create a comprehensive "Identity Graph" that links people to their digital footprints, phone numbers, and devices.

Positioned in the competitive KYC and identity intelligence market, SentiLink competes with firms like LexisNexis, Acuant, and Jumio, but distinguishes itself through real-time data aggregation and a focus on consumer privacy. Their core product suite includes Identity Search, Phone Intelligence, and Email Intelligence, which are critical for banks, lenders, and crypto platforms to comply with regulations.

The company has experienced significant growth, serving thousands of businesses globally and processing millions of identity checks annually. SentiLink’s culture is known for being engineering-driven, fast-paced, and remote-friendly, with a strong emphasis on data integrity and ethical AI use. Professionals want to work here because the company solves high-stakes problems in financial security while maintaining a modern, flexible work environment.

Data Scientist II - Big Data R&D, Identity Graph & KYC Role

Role Overview

In this role, you will design and deploy advanced machine learning models to enhance SentiLink’s Identity Graph and improve KYC accuracy. Your day-to-day work involves transforming massive, unstructured datasets into structured insights that detect fraud patterns and verify user identities in real time.

The impact of this role is direct and measurable: your models will reduce false positives in fraud detection, accelerate onboarding for financial clients, and strengthen the overall security of the digital economy. You will bridge the gap between raw big data and actionable business intelligence.

Detailed Responsibilities

• Develop and optimize machine learning algorithms for identity matching and fraud detection.
• Engineer scalable data pipelines to ingest and process terabytes of data from diverse sources.
• Collaborate with product teams to define metrics for KYC success and model performance.
• Conduct research and development on new data sources to expand the Identity Graph.
• Monitor model drift and implement automated retraining strategies to maintain accuracy.
• Document technical architectures and present findings to cross-functional stakeholders.

Day-to-Day Workflow

Your typical day starts with reviewing model performance dashboards to check for anomalies in fraud detection rates. You will then spend several hours writing Python code to refine data ingestion scripts or tune hyperparameters for a new classification model.

Mid-day often involves a stand-up meeting with the engineering team to discuss pipeline bottlenecks or data quality issues. Afterward, you might dive into deep work on a specific R&D project, such as testing a new graph neural network architecture for linking disparate identity records. The afternoon usually includes collaboration with product managers to align technical outputs with client requirements.

Tools and Technologies

SentiLink relies on a robust tech stack centered around big data processing and cloud infrastructure. Key tools include:

• Languages: Python (primary), SQL, Scala.
• Big Data Frameworks: Apache Spark, Kafka, Hadoop.
• Cloud Platforms: AWS (S3, EMR, Lambda, SageMaker).
• ML Libraries: Scikit-learn, TensorFlow, PyTorch, XGBoost.
• Databases: PostgreSQL, MongoDB, Redis.
• Visualization: Tableau, Plotly, Jupyter Notebooks.

Skills and Requirements

Technical Skills

Candidates must possess deep expertise in machine learning and big data engineering. You should be proficient in building end-to-end ML pipelines, handling unstructured data, and optimizing models for low-latency inference.

Strong command of SQL and Python is non-negotiable, along with experience in distributed computing frameworks like Spark. Knowledge of graph databases and graph neural networks is highly valuable for Identity Graph work.

Soft Skills

Effective communication is critical, as you must explain complex model behaviors to non-technical stakeholders. You need strong problem-solving abilities to navigate messy data scenarios and the initiative to drive R&D projects independently.

Teamwork is essential in a cross-functional environment where data scientists, engineers, and product managers collaborate daily to ship features quickly.

Experience Expectations

SentiLink typically targets candidates with 2–4 years of relevant experience in data science or machine learning engineering. A bachelor’s or master’s degree in Computer Science, Statistics, or a related field is expected.

While a specific GPA is rarely the sole deciding factor, a strong portfolio of projects demonstrating work with big data and ML models is crucial. Previous experience in fintech, KYC, or fraud detection is a significant advantage.

Salary and Benefits

The estimated salary range for a Data Scientist II at SentiLink in the New York market is $130,000 to $165,000 annually, plus equity and performance bonuses. Remote candidates may see slight adjustments based on location.

Benefits include comprehensive health, dental, and vision coverage, a 401(k) with company matching, and unlimited or flexible vacation policies. The company offers a remote/hybrid work model, a home office stipend, and a learning budget for conferences and courses.

There are strong opportunities for full-time conversion if this is an internship, with many interns transitioning into permanent roles based on project performance and team fit.

SentiLink Hiring Process

Step-by-Step Hiring Stages

1. Application: Submit your resume and portfolio via the company portal or LinkedIn.
2. Screening: A recruiter reviews your application for keyword matches and experience alignment.
3. Assignment: You may complete a take-home data challenge involving big data processing or model building.
4. Interviews: Typically includes a technical screen, a deep-dive coding interview, and a system design discussion.
5. Offer: Final negotiation and contract signing.

Application Timeline

Given the "Reposted Yesterday" status, the process is likely accelerated. From application to offer, the timeline typically spans 2–4 weeks. You should apply immediately to avoid missing the window.

Screening Methods

The ATS (Applicant Tracking System) scans for keywords like "Python," "Spark," "Machine Learning," and "KYC." Your resume must clearly highlight specific projects where you handled large datasets or built fraud detection models.

A portfolio with GitHub links to relevant code is highly recommended to demonstrate practical skills beyond just listing them.

Interview Preparation

Example Interview Questions

• "How would you design a system to link two disparate identity records with 95% confidence using only phone and email data?"
• "Explain how you would optimize a Spark job that is running slower than expected on a terabyte-scale dataset."
• "Describe a machine learning model you built for fraud detection and how you handled false positives."
• "What are the ethical considerations when building an Identity Graph for KYC purposes?"

How to Answer

Use the STAR method (Situation, Task, Action, Result) to structure your responses. Focus on the technical decisions you made and the measurable impact of your work.

For system design questions, start by clarifying constraints, then outline the architecture, and finally discuss trade-offs in latency versus accuracy.

What Recruiters Evaluate

Recruiters evaluate your technical depth, ability to solve real-world problems, and cultural fit. They look for candidates who can not only write code but also understand the business context of identity verification.

Key criteria include problem-solving agility, communication clarity, and a genuine passion for data-driven security solutions.

How to Get Selected

Practical Tips

• Tailor your resume to explicitly mention Identity Graph, KYC, and Big Data keywords.
• Prepare a GitHub repository with a project that demonstrates graph analysis or fraud detection.
• Research SentiLink’s specific products and mention them in your interview to show genuine interest.

Common Mistakes to Avoid

• Submitting a generic resume without specific metrics on model performance or data volume.
• Failing to explain the business impact of your technical projects.
• Ignoring the "Reposted Yesterday" urgency and applying late in the cycle.

How to Stand Out

To stand out, build a niche portfolio that simulates an identity matching problem. Network with current SentiLink employees on LinkedIn to get insights into the team’s current challenges. A tailored submission that addresses a specific gap in their current identity graph will demonstrate proactive thinking.

Final Thoughts

The Data Scientist II role at SentiLink is a high-impact opportunity to shape the future of digital identity and financial security. With the deadline Reposted Yesterday, the window to apply is narrow, but the potential for career growth is immense. Take action now, refine your application with specific big data and ML examples, and position yourself as the candidate who can solve SentiLink’s most complex identity challenges.

Frequently Asked Questions

Q: What is the salary for Data Scientist II - Big Data R&D, Identity Graph & KYC at SentiLink?
A: The estimated annual salary is between $130,000 and $165,000, plus equity and bonuses, depending on location and experience.

Q: How competitive is it to get hired at SentiLink?
A: It is moderately competitive, with a focus on candidates who have specific experience in fintech, fraud detection, or big data. The "Reposted Yesterday" status suggests they are actively seeking qualified talent quickly.

Q: What skills are most important for this role?
A: The most critical skills are Python, Apache Spark, machine learning model building, and experience with graph data structures or identity verification systems.