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Senior Data Scientist - Accounting United States, New York Jobs (On-site work)

3 Job Offers

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Senior Data Scientist - Payments
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Join Plaid in New York as a Senior Data Scientist for Payments. Leverage 5+ years of product-focused data science experience with SQL, Python, and A/B testing. You will derive insights, build ML models, and shape data-driven decisions for our financial API products, enjoying comprehensive benefit...
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United States , New York
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174000.00 - 260400.00 USD / Year
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Plaid
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Until further notice
Senior Forward-Deployed Data Scientist, AI Deployment
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Join our team as a Senior Forward-Deployed Data Scientist in New York City. You will partner directly with customers, deploying ML models and building scalable data pipelines using Python, TensorFlow, and SQL. This client-facing role requires strong technical expertise and offers competitive comp...
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United States , New York City
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145800.00 - 2178000.00 USD / Year
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Braze
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Until further notice
Senior Associate, Data Scientist - Recommendation & Personalization Systems
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Join Capital One as a Senior Associate Data Scientist, specializing in Recommendation & Personalization Systems. You will build advanced ML models using Python, AWS, and Spark to analyze billions of customer records. This role requires a quantitative degree and 2+ years of experience in data anal...
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United States , McLean; New York; San Jose
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135600.00 - 168900.00 USD / Year
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Capital One
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Until further notice
Explore high-impact Senior Data Scientist jobs in the dynamic field of accounting and finance. A Senior Data Scientist in this domain is a strategic leader who leverages advanced analytics, machine learning, and statistical modeling to solve complex financial challenges, drive efficiency, and uncover actionable insights from vast accounting and transactional data. This role sits at the intersection of data science, business strategy, and financial expertise, transforming raw numbers into strategic assets. Professionals in these senior positions typically own the end-to-end data science lifecycle. They are responsible for identifying key business problems, such as fraud detection, risk assessment, forecasting, process automation, and compliance monitoring. Their day-to-day involves researching and prototyping novel machine learning approaches, developing production-ready models, and deploying scalable solutions that integrate seamlessly with financial systems. A core responsibility is to design and run rigorous experiments to validate models and measure their impact on critical financial metrics. Collaboration is key; they work closely with accounting teams, finance executives, product managers, and engineers to translate business needs into technical specifications and ensure data-driven solutions are adopted effectively. Typical skills and requirements for these high-level jobs include an advanced degree (Master's or PhD preferred) in Data Science, Statistics, Computer Science, Applied Mathematics, or a related quantitative field. Candidates generally possess 5+ years of hands-on experience in building and deploying machine learning models in production environments. Technical mastery is essential, including deep proficiency in Python (with libraries like Pandas, scikit-learn, TensorFlow/PyTorch), SQL for complex data manipulation, and cloud platforms (AWS, GCP, Azure) for deployment. Beyond technical acumen, they must have a strong foundation in statistical inference, expertise in both supervised and unsupervised learning techniques, and experience with time-series analysis relevant to financial data. Success in these jobs also demands exceptional communication skills to explain complex models to non-technical stakeholders, a strong ownership mindset, and the ability to lead projects autonomously from conception to implementation. For those seeking to shape the future of finance through data, Senior Data Scientist jobs in accounting offer a challenging and rewarding career path at the forefront of technological innovation.

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