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Artificial Intelligence • Professional Services • Business Intelligence • Consulting • Cybersecurity • Generative AI
The role involves leveraging data analytics and AI techniques to support client needs, developing models, managing data teams, and building AI solutions. Key responsibilities include data processing, client collaboration, and presenting insights.
Top Skills:
AWSAzureGCPKerasLangchainNltkNoSQLPandasPythonScikit-LearnSemantic KernelSQL
Key Responsibilities
- Develop models, scores, and attributes that improve our clients’ bottom lines.
- Participate in data studies to analyze the performance of our products and their success in meeting key client performance metrics.
- Build predictive models, scores, and attributes that are marketable to our audience.
- Test our models, scores and attributes with a client’s test data and create a powerpoint with the sales team that showcases how our products work for each client.
- Work collaboratively with sales and the backend engineers to create innovative solutions that push our products forward.
- Engage with clients and internal teams to become an expert in our unique industry, understanding the real-world impact of our data science applications.
- Perform rigorous quality assurance to ensure data integrity and accuracy.
- Stay up to date with the latest advancements in AI and machine learning, applying innovative approaches to our evolving methodologies.
Required Skills & Experience
- 2+ years of experience in data science, AI, or machine learning (we prioritize skill over tenure).
- Proficiency in Python and its data science libraries (e.g., Pandas, NumPy, Scikit-learn, Matplotlib).
- Experience developing predictive models and scores to drive business outcomes.
- Strong data visualization and storytelling skills, with the ability to communicate insights to both technical and non-technical stakeholders.
- Proficiency with machine learning frameworks, including TensorFlow, PyTorch, or AutoGluon.
- Understanding of how data science contributes to revenue growth and business strategy.
- A collaborative mindset with a strong desire to learn and innovate.
- Ability to thrive in a fast-paced, evolving environment where adaptability is key.
What you need to know about the NYC Tech Scene
As the undisputed financial capital of the world, New York City is an epicenter of startup funding activity. The city has a thriving fintech scene and is a major player in verticals ranging from AI to biotech, cybersecurity and digital media. It also has universities like NYU, Columbia and Cornell Tech attracting students and researchers from across the globe, providing the ecosystem with a constant influx of world-class talent. And its East Coast location and three international airports make it a perfect spot for European companies establishing a foothold in the United States.
Key Facts About NYC Tech
- Number of Tech Workers: 549,200; 6% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Capgemini, Bloomberg, IBM, Spotify
- Key Industries: Artificial intelligence, Fintech
- Funding Landscape: $25.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Greycroft, Thrive Capital, Union Square Ventures, FirstMark Capital, Tiger Global Management, Tribeca Venture Partners, Insight Partners, Two Sigma Ventures
- Research Centers and Universities: Columbia University, New York University, Fordham University, CUNY, AI Now Institute, Flatiron Institute, C.N. Yang Institute for Theoretical Physics, NASA Space Radiation Laboratory

