- • Gather, interpret, and manipulate structured and unstructured data to enable advanced analytical solutions
- • Develop scalable, automated solutions using machine learning, simulation, and optimization
- • Select modeling techniques and technologies based on data limitations, application, and business needs
- • Develop and deploy models within the Model Development Control and Model Risk Management frameworks
- • Compose technical documents for knowledge persistence, risk management, and technical review audiences
- • Assess business needs and recommend analytical and modeling projects
- • Prioritize analytics and modeling problems with business and analytics leaders
- • Build and maintain reusable, production-quality algorithms and supporting code
- • Translate business requests into analytical questions, execute analyses or modeling, and communicate actionable recommendations to non-technical colleagues
- • Manage project milestones, risks, and impediments; escalate issues that could limit success
- • Develop deployment best practices with Data Engineering and IT
- • Maintain awareness of cutting-edge techniques, technologies, and methodologies
- • Mentor junior data scientists
- • Participate in internal communities supporting data science technology and culture
- • Identify, measure, monitor, and control risks in accordance with policies and procedures
Requirements
- Bachelor's degree in mathematics, Computer Science, Statistics, Science, Engineering, or a quantitative field; OR 4 years of relevant education and/or experience; and 6+ years of experience in predictive analytics or data analysis
- Advanced degree in mathematics, computer science, statistics, science and engineering, AI, or a similar quantitative discipline and 4+ years of experience in predictive analytics or data analysis
- 4+ years of experience training and validating statistical, physical, machine learning, and other advanced analytics models
- 4+ years of experience using Python for statistical analysis and/or building and scoring AI/ML models
- Experience writing transparent, well-documented, and commented code
- Strong experience querying and preprocessing structured and/or unstructured data using SQL, HQL, NoSQL, or similar query languages
- Skill in ad-hoc descriptive, diagnostic, and inferential statistics
- Understanding of latency, cost, and reliability constraints in AI solution design
- Ability to assess and articulate regulatory implications across risk stripes
- Experience documenting and statistically validating models for risk management
- Advanced experience with supervised modeling, including regression, discriminant analysis, support vector machines, decision trees, and forest models
- Advanced experience with unsupervised modeling, including k-means, hierarchical/agglomerative clustering, neighbors algorithms, and DBSCAN
- Expertise developing LLMs and agentic systems using frameworks such as LangChain/LangGraph, AgentCore, VertexAI, MCP, or others
- Proven experience with prompt engineering, tuning and post-training, multi-agent systems, agent optimization and tool use, RAG, context optimization, observability, and monitoring
- MLOps integration experience facilitating production-scaled AI solutions in AWS or GCP
- Experience communicating analytical and modeling results to non-technical business partners
- Experience guiding and mentoring junior technical staff
- Relocation assistance is not available
- Must not require visa sponsorship or immigration support now or in the future
Core Competencies
Demonstrates expertise in predictive analytics and data analysis, with a strong focus on developing and deploying machine learning models and algorithms. Proficient in communicating complex analytical results to non-technical stakeholders and mentoring junior data scientists.
Highest-signal resume keywords
- Predictive Analytics
- Machine Learning Model Development
- Python for Statistical Analysis
- SQL Querying and Preprocessing
- MLOps Integration in AWS or GCP
ATS Optimization Keywords
Hard Skills
- Predictive Analytics
- Machine Learning
- Statistical Analysis
- Model Validation
- Algorithm Development
- Data Manipulation
- Model Risk Management
- Supervised Modeling
- Unsupervised Modeling
- Prompt Engineering
Soft Skills
- Communication
- Mentoring
- Project Management
- Problem Solving
- Collaboration
Industry Keywords
- Data Science
- Risk Management
- Model Development Control
- Data Engineering
- AI Solutions
Tools & Technologies
- Python
- SQL
- HQL
- NoSQL
- LangChain
- LangGraph
- AgentCore
- VertexAI
- AWS
- GCP