• 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

• 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

• 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 

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What to Expect When Applying

Whether this is your first time applying to Palm Tree or you’ve connected with us before, you are welcome to use this portal to submit an updated résumé, cover letter, or other materials. Our recruiting team will thoughtfully incorporate your most recent information into your existing application profile. And yes—we do read cover letters. In fact, the cover letter is a great place to demonstrate why you're qualified for a position, even if you do not meet all requirements.

Application Confirmation
After submitting your application, you will receive an email confirming that we’ve received your materials.

Initial Review
Once your application has been reviewed and added to our active candidate database, you will receive a second confirmation email. Timing for this step can vary based on current hiring needs and priorities, so we appreciate your patience.

Note: If a role is marked as an “immediate” opening, the posting will typically outline specific timelines for each stage of the process, including a potential start date.

Screening
If and when a suitable opportunity arises, a member of our hiring team will reach out to schedule an introductory conversation. The timing of this step is demand-driven and can vary.

Interviews
Qualified candidates will be invited into a formal interview process. As with earlier stages, timing may vary depending on hiring priorities and role requirements.

While we do carefully review every application, we are unable to provide individual feedback to all candidates due to application volume. We value transparency and sincerely appreciate your understanding.

Important Notice
Palm Tree is not currently engaging outside recruiters or headhunters for this search. Unsolicited résumé submissions from third parties may inadvertently disqualify a candidate. All interested and qualified candidates should apply directly through this portal.