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Senior Data Scientist - Accounting United States, Menlo Park Jobs (Hybrid work)

3 Job Offers

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Senior Data Scientist, Fraud
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Join Robinhood as a Senior Data Scientist in Fraud, based in Menlo Park. Design and deploy real-time ML models using Python and advanced frameworks to detect fraud, mitigate risk, and protect users. Leverage 5+ years of experience in data science to directly impact security and compliance. Enjoy ...
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United States , Menlo Park
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187000.00 - 220000.00 USD / Year
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Robinhood
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Until further notice
Senior Data Scientist, Experimentation
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Join Robinhood in Menlo Park as a Senior Data Scientist on the Experimentation Platform. You will shape the statistical foundations of our A/B testing systems, using Python/R and advanced methods like causal inference. This high-impact role involves building scalable tools and evangelizing best p...
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United States , Menlo Park
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187000.00 - 220000.00 USD / Year
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Robinhood
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Until further notice
Senior Data Scientist, Product
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Join Robinhood as a Senior Data Scientist in Menlo Park. Apply your expertise in statistical analysis, machine learning, and Python/SQL to drive product strategy and business impact. You will design experiments, build predictive models, and communicate insights to senior leadership. Enjoy top-tie...
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United States , Menlo Park
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Salary
179000.00 - 210000.00 USD / Year
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Robinhood
Expiration Date
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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