Summary
Concord Advice is a dynamic fintech company headquartered in the NYC 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, unstructured setting that demands creativity, analytical thinking, and cross-functional collaboration. If you’re a problem-solver who embraces ambiguity and enjoys tackling challenges, join us in shaping the future of fintech!
Key Qualifications
Job Description
As a Data Scientist Intern at Concord Advice, you will:
• Thrive in an unstructured environment and enjoy tackling complex, ambiguous problems. Have a consultative mindset to break down challenges into root
causes, develop structured analysis plans, and identify the necessary data to drive insights.
• Collaborate as a member of the analytic team, with senior management and IT team to design models, perform data mining, and conduct statistical research.
• Enhance automation in machine learning, programming, and business operations.
• Build, test, and monitor various machine learning models.
• Work with Azure cloud computing and MLOps pipeline to create end-to-end automated machine learning.
• Identify opportunities in data to drive company strategy, products, and solutions.
• Participate in the development of data infrastructure, data governance, and various business intelligence tools and products
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