Senior Data Scientist

This is a fully remote position, open to applicants in United States.

📋 Description

• Analyze large and intricate data sets to address unstructured challenges using analytical and statistical methodologies for various products independently.

• Lead the process of sourcing, ingesting, and cleansing data sets in preparation for analysis.

• Support senior data scientists in streamlining and scaling data cleaning operations.

• Ensure data stability, taking into account complex data drift in both development and production environments.

• Construct econometric, statistical, and machine learning models for tasks such as classification, clustering, pattern analysis, sampling, and simulations.

• Contribute complex code to the model repository and facilitate the promotion of intricate models into production.

• Develop champion/challenger models and modify them as needed.

• Establish a framework for creating self-healing models.

• Select and fine-tune models based on performance, reliability, stability metrics, and feedback from the business.

• Craft educational materials for data users regarding model refinement.

• Generate model outputs for business discussions to showcase outcomes, impact, and business value.

• Mentor junior team members in producing accessible model outputs.

• Participate in stakeholder meetings to address concerns, identify opportunities, and discuss production challenges.

• Collaborate with senior data scientists to innovate new research methods and evaluate adaptations based on client requirements.

• Review code for efficiency, accuracy, and adherence to best practices.

• Comply with company risk and regulatory standards, policies, controls, and risk appetite.

• Identify risk-related issues that require escalation to management.

• Foster an environment that promotes diversity and aligns with the Bank's brand.

• Uphold internal control standards and execute audit and regulatory action items.

• Perform other related tasks as assigned.

⛳️ Requirements

• Bachelor's degree with a minimum of 5 years of relevant experience, or alternatively, a combined total of 9 years of higher education and/or work experience, including at least 5 years of relevant experience.

• Familiarity with various statistics and data science principles, including AB testing, sample selection, hypothesis testing, and modeling bias.

• Proficient in relevant statistical software, programming languages, and tools.

• Experience with diverse hybrid databases, both on-premises and in the cloud.

• Intermediate knowledge of Structured Query Language (SQL) and Not Only Structured Query Language (nSQL).

• Intermediate understanding of modeling techniques such as Bayesian Modeling, Classification models, Cluster analysis, Neural Networks, Non-parametric methods, and Multivariate statistics.

• Experience in analyzing substantial data sets.

• A Master's degree or Doctorate in Statistics, Economics, Finance, or a related field is preferred.

• Proficient in econometric/statistical techniques, including time-series analysis, panel data methods, and logistic regression.

• Practical experience with relevant statistical software, programming languages, and tools.

🏝️ Benefits

• Remote work arrangement