5+ years of experience in predictive modeling within corporate or financial settings
Proven track record of applying advanced statistics and machine learning for business impact
Expertise in statistical analysis, Python, R, and data science frameworks
Strong collaboration skills with operational teams for data context understanding
In-depth knowledge of financial datasets and regulatory constraints
Ability to communicate complex findings to non-technical audiences
Execution-focused mindset with an emphasis on analytical results
Responsibilities
Develop and train advanced predictive models for anomaly detection and risk mitigation
Conduct deep statistical analysis and data wrangling in large-scale environments
Rigorously validate model accuracy and ensure compliance with financial standards
Collaborate with business leaders to transform raw financial data into training datasets
Establish KPIs related to model accuracy and prediction precision
Benefits
Opportunity to lead enterprise AI initiatives
Collaborative work environment with cross-functional teams
Focus on high-impact decision-making and risk reduction
Engagement with cutting-edge statistical and machine learning techniques
Professional growth in a dynamic financial landscape
Full Job Description
Position Summary
The AI Data Scientist will own the modeling and statistical lifecycle of enterprise AI initiatives. The role will partner with business operations to structure financial data, build predictive models, and ensure AI investments deliver high-accuracy insights that reduce risk and improve decision-making. The role requires a rigorous quantitative expert who can balance complex statistical analysis with strict financial regulatory standards and drive alignment across business and technology teams.
Key Responsibilities
Develop and train advanced predictive models for anomaly detection, workflow forecasting, and risk mitigation
Perform deep statistical analysis and data wrangling within large-scale enterprise environments
Validate model accuracy rigorously, test for bias, and ensure all outputs meet strict financial compliance standards
Partner with business leaders to understand the nuance of financial data and transform raw inputs into training datasets
Establish KPIs tied to model accuracy, prediction precision, and false-positive reduction
Qualifications
5+ years of experience building and validating predictive models in a corporate or financial environment
Demonstrated ability to apply advanced statistics and machine learning to deliver measurable business outcomes
Deep expertise in statistical analysis, Python, R, and data science frameworks
Ability to work effectively with operational teams to understand data context without needing constant translation
Strong understanding of financial datasets and the regulatory constraints surrounding automated decision-making
Ability to present complex quantitative findings to non-technical stakeholders
Operator mindset with a focus on execution and analytical outcomes
