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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in analyzing complex datasets and developing machine learning models, with a strong focus on Generative AI solutions and responsible AI practices. Proficient in translating analytical insights into actionable business recommendations while ensuring model governance and data privacy.
Highest-signal resume keywords
Machine Learning Model DevelopmentGenerative AI SolutionsPython ProgrammingStatistical AnalysisData Governance
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Machine LearningFeature EngineeringModel EvaluationStatistical AnalysisPredictive ModelingData TransformationSQLData Science LibrariesGenerative AIPrompt Engineering
Soft Skills
Analytical SkillsProblem-SolvingCommunication SkillsMentoringCollaboration
Tools & Technologies
AWSAzureGCPScikit-learnPyTorchTensorFlowMLOpsLLMOps
Industry Keywords
Responsible AIData PrivacyModel GovernanceData CleansingData Integration
Tech Stack
Tools & technologiesAWSAzureGoogle Cloud PlatformPythonPyTorchScikit-LearnSQLTensorflow
About the role
Key responsibilities & impact- Analyze large and complex datasets using statistical, machine learning, and advanced analytical techniques
- Identify patterns, generate insights, and solve business problems
- Design, develop, evaluate, and optimize machine learning models
- Perform feature engineering, model validation, performance testing, and ongoing monitoring
- Develop and evaluate Generative AI solutions using foundation models
- Apply prompt engineering, retrieval-augmented generation, embeddings, semantic search, and agentic AI techniques
- Develop evaluation frameworks and experimentation approaches to measure model quality, accuracy, relevance, safety, and business impact
- Evaluate alternative approaches and communicate technical trade-offs and recommendations
- Acquire, cleanse, transform, and integrate structured and unstructured data
- Partner with engineering teams to deploy data science and AI solutions into production
- Support model lifecycle management, monitoring, reproducibility, performance optimization, and scalability
- Collaborate with business and technology partners to define problems and identify data science approaches
- Translate analytical findings into actionable recommendations
- Communicate complex concepts to technical and non-technical audiences
- Apply controls and governance practices related to model risk, explainability, data privacy, security, bias, and responsible AI use
- Mentor less-experienced data scientists
- Contribute to technical design and methodology decisions
- Help establish reusable data science, machine learning, and AI best practices
Requirements
What you’ll need- 3+ years of relevant experience
- Bachelor's degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, or equivalent
- Advanced programming skills in Python and common data science/ML libraries
- Experience with SQL and large, complex datasets
- Experience preparing, transforming, and analyzing structured and unstructured data
- Experience applying statistical analysis, predictive modeling, machine learning, feature engineering, experimentation, and model evaluation
- Hands-on experience developing or evaluating Generative AI and LLM-based solutions, including RAG, embeddings, semantic search, prompt engineering, and/or agentic AI
- Experience with scikit-learn, PyTorch, or TensorFlow
- Experience integrating internally hosted or third-party foundation models
- Experience with AWS, Azure, or GCP
- Familiarity deploying analytical, machine learning, or AI solutions
- Familiarity with MLOps/LLMOps practices such as monitoring, versioning, reproducibility, and observability
- Knowledge of Responsible AI, model governance, data privacy, security, and handling sensitive data and PII
- Strong analytical, problem-solving, and communication skills
- Ability to translate complex analytical findings into meaningful business insights
- Ability to provide technical guidance to other data scientists or analysts
Benefits
Comp & perks- 20 paid time off days
- 11 paid holidays
- 8 hours of volunteer time off yearly
- 401K retirement savings plan with matching and company contributions
- Student loan pay downs
- 529 educational save up assistance programs
- Tuition reimbursement
- Employee stock purchase plan
- Financial learning center and financial coach access
- Medical, dental and vision insurance
- Employee, spouse and child life insurance
- Short- and long-term disability
- Pre-tax Health Savings Account with employer contributions
- Healthcare FSA
- Critical illness, accident and hospital indemnity insurance
- Total well-being program
- Adoption, surrogacy and fertility assistance
- Paid parental and caregiver leave
- Dependent Day Care FSA
- Back-up child and adult/elder care days
- Childcare discounts
- Mentally Fit Employee Assistance Program
- Subsidized and discounted Weight Watchers® program
- Other employee discount programs
- Travel allowances, depending on role
- Relocation assistance, depending on role
- Signing bonus, depending on role
- Equity, depending on role
- Annual incentive plan