Data Scientist Intern — Concord Advice

Summary

Concord Advice is a dynamic fintech company headquartered in the New Jersey area, specializing in delivering cutting-edge analytical and technical solutions for financial organizations. We design and implement innovative technology solutions, including CRM platforms, underwriting engines, auction-based online lead bidding systems, omni-channel customer engagement strategies, payment technologies, and bank integration services.

Our strategic investments in cloud infrastructure and MLOps pipelines enable us to leverage state-of-the-art language AI — from large-language-model (LLM) agents and retrieval-augmented generation to proven NLP capabilities such as named-entity recognition, intent detection, and sentiment analysis — to create intelligent, real-time, and automated customer experiences.

As a fast-growing, entrepreneurial, and collaborative firm, Concord Advice provides an immersive, hands-on environment where innovation meets business impact. Our team thrives in a dynamic setting that rewards creativity, analytical thinking, and cross-functional collaboration. If you're a problem-solver who enjoys tackling open-ended challenges, join us in shaping the future of fintech!

Job Description

As a Data Scientist Intern at Concord Advice, you will:

• Collaborate as a member of the analytics team, working alongside senior management and IT to design models, perform data mining, and conduct statistical research.
• Work closely with open banking data to support loan term optimization, cashflow underwriting, and revenue improvement.
• Build end-to-end automated machine learning workflows using Azure cloud computing and our MLOps pipeline.
• Contribute to the development of an LLM-assisted machine learning system that classifies bank transactions, helping improve the accuracy and coverage of our existing labeling framework.
• Support firm-wide efforts to centralize data definitions and institutional knowledge by helping build retrieval-augmented generation (RAG) workflows, MCP servers, and semantic layers.
• Take ownership of complex, ambiguous problems in a fast-moving environment, applying a consultative mindset to break challenges down into root causes, develop structured analysis plans, and identify the data needed to drive insights.

Key Qualifications

• BA/MS in a business-related field with a focus on machine learning.
• Comfortable working with a range of machine learning and statistical packages in Python, along with databases and reporting tools.
• Solid grounding in the foundational concepts behind a variety of advanced ML algorithms.
• Familiarity with the Azure cloud platform and experience using Azure services to support data science, machine learning, analytics, and production-oriented workflows.
• Outstanding communication skills (both technical and non-technical) and a proven ability to work effectively with multiple stakeholders across a variety of business units.
• Self-motivated, vocal, and proactive, with demonstrated creative and critical thinking capabilities.

Good to Have

• Working knowledge of modern AI and analytics engineering patterns, including retrieval-augmented generation (RAG), dbt, and semantic modeling.
• Hands-on experience with NLP modeling techniques such as text classification and named-entity recognition (NER).
• Exposure to credit underwriting or risk modeling within a lending business.