Senior Data Scientist at Snowflake working on predictive modeling and financial forecasting initiatives. Leading high - impact projects at the intersection of ML and business strategy.
About the role
- Data Scientist Manager analyzing data for marketing and risk management at Ameriprise Financial. Identify and implement analytical solutions while collaborating cross-functionally.
Responsibilities
- Identify, develop and implement complex analytical solutions leveraging tools such as predictive modeling, advanced machine learning techniques, simulation, optimization solutions, etc., with respect to credit card, lending and cash products for marketing and risk management purposes.
- Manage dataset creation including data extraction, derived and dependent variable creation, and data quality control processes for analytics, model development, and validation.
- May monitor execution of analytical solutions, including criteria specification, data sourcing, segmentation, analytics, selection, delivery, and back-end data capture results.
- Consult and coordinate campaign execution for direct to client campaigns.
- Identify and execute targeting and optimization opportunities.
- Collaborate with business leaders and/or analysts to provide analytical thought leadership and support for business problems.
- Identify and interpret business needs, define high-level business requirements, strategy, technical risks, and scope.
- Develop, document, and communicate business-driven analytic solutions and capabilities, translating modeling and analytic output into understandable and actionable business knowledge.
- Ensure adherence to data and model governance standards that are set and enforced by industry standards and/or enterprise and business unit data governance policies and leaders.
Requirements
- Master's degree or equivalent in Quantitative Discipline (i.e. Finance, Statistics, Computer Science, Actuarial Science, Economics, Engineering, etc.)
- 3 - 5 years relevant experience required
- Knowledge of advanced statistical concepts and techniques; skilled in linear algebra.
- Experience conducting hands-on analytics projects using advanced statistical methods such as generalized regression models, Bayesian methods, random forest, gradient boosting, neural networks, machine learning, clustering, or similar methodologies.
- Experience with statistical programming (SAS, R, Python, SQL etc.) & data visualization software in a data-rich environment.
- Proven ability to present/communicate complex, technical materials in a way that facilitates decision making and drives outcomes; ability to communicate to less technical partners.
- Proven ability to apply both strategic and analytic techniques to provide business solutions and recommendations.
- Ability to work effectively in a collaborative team environment.
Benefits
- vacation time
- sick time
- 401(k)
- health insurance
- dental insurance
- life insurance
Job title
Job type
Experience level
Salary
Degree requirement
Tech skills
Location requirements
Data Manager overseeing various research and advisory projects at Busara and managing project staff. Collaborating with academic researchers and advisory clients while ensuring project execution and management.
Graduate Program participant supporting Australia's Defence Industry through hands - on projects and professional development initiatives.
Data Science Intern leveraging skills in statistics and programming for data - driven projects at Revolve. Collaborating with marketing and operations for insightful analytics and strategy recommendations.
Senior AI & Data Scientist leading advanced analytical model development for tech company. Ensuring robust data architecture and deploying AI solutions from analysis to production.
Senior Data Scientist responsible for enhancing mapping and routing solutions at Vay. Utilizing data science and machine learning to improve navigation in urban mobility systems.
Data Scientist transforming complex data into valuable insights for adp MERKUR GmbH. Develops machine - learning models and collaborates with stakeholders for data - driven decisions.
Senior Real World Data Scientist providing statistical and epidemiological expertise in nutrition and health research. Analyzing large scale observational data and guiding project teams in statistical methodologies.
Senior Data Scientist at LexisNexis Risk Solutions applying machine learning and AI for government services. Collaborating with a diverse team to solve meaningful problems.
Clinical Data Manager supporting the biospecimen and clinical data management for WVU Cancer Institute. Engaging in data collection, management, and reporting for research and quality assurance.