Senior Analyst, Data & Analytics (AI)

Achieve Your Potential

The Senior Analyst, Data & Analytics (AI) role at Palm Tree offers a unique blend of technical expertise and business acumen. This role is designed for individuals who thrive in a dynamic, fast-paced environment where they can contribute to the strategic growth of private equity portfolio companies.

Responsibilities

• Build and deploy supervised and unsupervised ML models including forecasting (ARIMA, VAR, gradient boosting), classification, clustering, and anomaly detection across client datasets
• Design and implement NLP pipelines for topic modeling, text classification, and unstructured data analysis on operational and financial records
• Develop and maintain experimentation frameworks including A/B testing, lift analysis, and causal inference to evaluate operational interventions
• Translate model outputs into actionable business recommendations for operations, finance, and commercial leadership teams
• Apply imbalance correction, cross-validation, and threshold optimization to ensure model reliability in production environments
• Design and build scalable ETL/ELT pipelines using Azure Data Factory, Python, and cloud-native tools to ingest data from ERP, CRM, and operational source systems
• Write production-grade SQL to model, transform, and validate data across complex multi-table schemas
• Architect cloud data infrastructure on Azure (Azure SQL, ADLS, ADF) and Snowflake to support analytics and ML workloads
• Reduce data latency and improve pipeline reliability through automated orchestration and monitoring
• Develop and maintain Power BI semantic models, DAX measures, and executive dashboards that surface operational and financial KPIs
• Design KPI reporting frameworks providing leadership teams with real-time visibility into performance across inventory, revenue, and operations
• Implement row-level security, governance controls, and data quality checks within BI environments
• Partner directly with portfolio company stakeholders to define analytical requirements, success metrics, and delivery frameworks
• Translate complex business questions into data models, ML problem statements, and analytical frameworks
• Lead working sessions with business and technical stakeholders to align on priorities and communicate findings clearly
• Independently manage analytics workstreams including scoping, effort estimation, and delivery execution
• Mentor and support junior analysts across client engagements
• Contribute to internal knowledge development including ML frameworks, data architecture standards, and reusable analytics assets
• Support development of AI/ML methodologies and delivery accelerators within the practice

Requirements

• 3-5+ years of experience in data analytics, data science, or data engineering roles
• Proficiency in Python for ML model development (scikit-learn, statsmodels, NumPy, Pandas) and data pipeline automation
• Strong SQL proficiency including CTEs, window functions, subqueries, and complex joins across large-scale schemas
• Hands-on experience building and deploying machine learning models in production or near-production environments
• Experience with forecasting methodologies (ARIMA, VAR, gradient boosting) and/or NLP techniques (LDA, text classification)
• Demonstrated ability to design and evaluate controlled experiments including A/B testing and lift analysis
• Experience building Power BI models, DAX measures, and dashboards for operational or financial reporting
• Strong communication skills with the ability to translate technical findings to non-technical business audiences
• Ability to independently manage multiple workstreams in fast-paced consulting or advisory environments
• Experience working within private equity portfolio company environments or management consulting
• Hands-on experience with Azure Data Factory, Azure SQL, ADLS, or Snowflake for cloud data infrastructure
• Exposure to ERP systems such as AS/400, NetSuite, QuickBooks, or similar platforms
• Familiarity with BI tools such as Tableau, Power BI, or Databricks for analytical delivery
• Experience with R for statistical modeling or time-series analysis
• Graduate degree in Analytics, Statistics, Computer Science, Economics, or a related quantitative field

Qualifications

• Base salary range of $100,000-$125,000, with performance-based bonus opportunities
• Comprehensive benefits package including medical, dental, and vision insurance
• Competitive 401(k) program with employer matching contributions
• Hybrid work environment with access to offices in Los Angeles, Chicago, and New York
• Unlimited paid time off (PTO)
• Opportunities for career advancement within a merit-based, entrepreneurial culture

Benefits

• Medical, dental, and vision insurance
• Competitive 401(k) program with employer matching contributions
• Hybrid work environment with access to offices in Los Angeles, Chicago, and New York
• Unlimited paid time off (PTO)
• Opportunities for career advancement within a merit-based, entrepreneurial culture

Schedule

• Hybrid work environment

Pay

• Base salary range of $100,000-$125,000, with performance-based bonus opportunities