Senior Data Scientist

RBC•New York, NY

2d•Hybrid

About The Position

RBC Capital Markets LLC seeks a Senior Data Scientist in New York, NY to utilize advanced statistical and machine learning techniques, including regression, Bayesian methods, Monte Carlo simulation, NLP, reinforcement learning, and hypothesis testing, to address specific use cases such as clinical trials and price prediction models. Analyze diverse data sets—structured, unstructured, news, transcripts, social media, and geospatial data—to generate actionable insights for strategic decision-making. The role involves researching and evaluating new data science methodologies, developing predictive models, and enhancing data collection processes to create proprietary insights. Will manipulate large-scale data using advanced engineering techniques, work with data pipelines from various sources, and collaborate with research, technology, and business teams to deliver analytics, visualizations, and innovative applications. Stay up to date with emerging trends in machine learning and data science, contribute to research reports, and develop models that can be deployed in production environments. Additionally, the role includes building and maintaining a repository of models and data assets, translating complex technical solutions into client-facing products, and continuously improving model performance through retraining and troubleshooting. Contribute to advancing organizational data science capabilities and harnessing AI to solve complex business problems. Hybrid work is permitted.

Requirements

Master’s degree in Statistics, Data Science, Computer Science, Applied Mathematics, or a related field plus 3 years of experience, or, in the alternative, a PhD degree with coursework in the field of statistics.
Special skills in data science coding.
Special skills in statistical modelling.
Special skills in data science/machine learning algo.
Special skills in natural language processing.
Special skills in cloud-based technology.
Special skills can be gained through either employment or educational experience.

Nice To Haves

Actuarial Modeling
Big Data Management
Commercial Acumen
Data Mining
Data Science
Decision Making
Machine Learning (ML)
Natural Language Processing (NLP)
Predictive Analytics
Python (Programming Language)

Responsibilities

Utilize advanced statistical and machine learning techniques, including regression, Bayesian methods, Monte Carlo simulation, NLP, reinforcement learning, and hypothesis testing, to address specific use cases such as clinical trials and price prediction models.
Analyze diverse data sets—structured, unstructured, news, transcripts, social media, and geospatial data—to generate actionable insights for strategic decision-making.
Research and evaluate new data science methodologies.
Develop predictive models.
Enhance data collection processes to create proprietary insights.
Manipulate large-scale data using advanced engineering techniques.
Work with data pipelines from various sources.
Collaborate with research, technology, and business teams to deliver analytics, visualizations, and innovative applications.
Stay up to date with emerging trends in machine learning and data science.
Contribute to research reports.
Develop models that can be deployed in production environments.
Build and maintain a repository of models and data assets.
Translate complex technical solutions into client-facing products.
Continuously improve model performance through retraining and troubleshooting.
Contribute to advancing organizational data science capabilities.
Harness AI to solve complex business problems.