Data & Analytics; D&A) Developer

Position: Data & Analytics (D&A) Developer
Payrate: $40.00 - $50.00/hr summary:
We are seeking a curious, analytically sharp, and digitally passionate Data Scientist to join our HDPE Operations & Strategy team – a team where collaboration and participative leadership are not just words, but the way we work every day. This is your opportunity to create real impact from day one. As a core member of our HDPE team, you will be at the forefront of our engineering vision — where data intelligence and AI-powered tools redefine how we manage, predict, and operate across Company’s global business.

Key Responsibilities:

Data Analysis & Intelligence:
Analyze quality data from multiple enterprise systems (SAP, Salesforce, Databricks, Power BI, labor systems, finance data) to identify patterns, gaps, and opportunities for data-driven improvements Work with Program Managers and/or Operations leaders to define which data assets are relevant for business use cases and specify how data from different systems should be accessed, interpreted, and used Transform structured/unstructured datasets (often 100k+ rows) into actionable insights Conduct data quality checks and identify/resolve data defects and abnormalities across enterprise platforms AI/ML Model Development & Deployment:
Develop and validate Machine Learning models that support demand forecasting, scenario modeling, and predictive use cases for short-term and long-term business goals Document analytical findings, model performance, and data definitions clearly to ensure transparency and reproducibility across the team Pipeline Collaboration & Development:
Experience working with Data Engineers to ensure data requirements are correctly implemented; ability to build and maintain Python-based data pipelines for ETL, model training, and automated forecasting workflows Translate business technical data challenges into concrete data science and AI/ML problem statements, acting as the domain-aware bridge between Engineering/Operations and the Digital team Leverage Large Language Models (LLMs) and prompt engineering to build intelligent tools that augment human decision-making and automate workflows Scenario Planning & Project Execution Analytics:
Design and execute scenario planning models to test business assumptions (demand forecasts, resource capacity, cost projections) and evaluate "what-if" outcomes for strategic decision-making Track project execution data across P6 (Primavera) and other project management systems, linking planning assumptions to actual execution performance Support variance analysis between planned assumptions (forecast hours, budgets, timelines) and actual project execution data to identify gaps, root causes, and trends Build automated tracking solutions that monitor assumption validity as projects progress through lifecycle stages (planning → design - execution → closeout) Collaborate with Program Managers to refine planning assumptions based on execution learnings and historical pattern analysis Provide data pipeline and data to build executive dashboards that visualize assumption-to-execution alignment, highlighting projects at risk due to assumption breakdown Existing Data Ecosystem & Optimization:
Review and analyze existing dashboards, models, and data pipelines to understand design patterns, business requirements, and data flows Read and interpret SQL queries, business logic, and semantic models embedded in current reports and analytical systems Understand underlying data structures and prepared data sources to support maintenance and enhancement Identify opportunities to optimize or consolidate existing reporting and modeling assets Maintain consistency with established data standards and best practices Business Stakeholder

Collaboration:

Translate complex data findings and model outputs into clear, actionable business insights for both technical and non-technical audiences Resolve customer and internal user queries related to model outputs, data insights, or data defects Support the Operations team in delivering centralized data analysis-based reporting solutions (including KPI), providing harmonized insights and KPIs to business stakeholders across Company's global business lines Innovation & Continuous Improvement:
Collaborate closely with cross-functional Data analysts and Data engineers to ensure data requirements are correctly understood and implemented at pipeline and infrastructure level Build and maintain a deep understanding of Semantic Data Models to ensure consistent data…