Data & Analytics (D&A) Developer II

Lancesoft; Greenville (SC); Hybrid; USD 143,270,000 - 159,890,000; Full time

Job summary

Lancesoft in Greenville, SC is seeking a Data & Analytics Developer for a 12-month hybrid role. You will bridge engineering data knowledge with business planning, building AI-powered tools and scenario models to optimize HDPE operations.

Responsibilities include data analysis, ML model development, and data integration across SAP, Salesforce, and Databricks. You will collaborate with IT and operations to deliver actionable insights and predictive outcomes for global stakeholders.

Qualifications

• Proficiency in Python for data analysis and ML development.
• Experience with multi-scenario planning and What-If analysis.
• Background in ML frameworks (scikit-learn, XGBoost).
• Strong SQL querying and data manipulation skills.

Responsibilities

• Data analysis and intelligence to drive insights.
• Build scenario planning models and test critical business assumptions.
• Collaborate with Data Engineers to ensure data requirements are implemented.

Skills

Python

Scenario Planning

Machine Learning

SQL

Statistical Analysis

Data Exploration

Data Cleaning

Data Integration

Anomaly Detection

Semantic Data Models

Forecasting

Large Language Models

Reverse Engineering

SQL Query Analysis

Data Source Understanding

Pipeline Collaboration

Tools

SAP

Salesforce

Databricks

ERP/CRM

Job description

Job Title: Data & Analytics (D&A) Developer Job Duration: 12 Months Location: Greenville, SC, 29615 (Hybrid) Pay Rate: $50.00 - 55.80 USD per hour on W2 Shift Timing: Monday to Friday, first shift

Job Description: 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 global business. You will act as the critical bridge between our Engineering domain data knowledge, business planning, operations, and our IT execution team defining what data we need, how it should be structured and used, and what AI/ML solutions can unlock the most value. You will support centralized business operations and program reporting that delivers harmonized insights and predicted range of outcomes to business stakeholders worldwide. You will build scenario planning models that test critical business assumptions and track project execution through P6 and enterprise systems, identifying gaps between plan and reality to drive proactive decision-making. This role will be critical in efforts to optimize HDPE Operations program management activities

Responsibilities

• o Python: Strong proficiency in data analysis, statistical modeling, and ML development (pandas, numpy, scikit-learn, scipy, curve fitting, object-oriented programming).
• o Scenario Planning & What-If Analysis: Ability to build multi-scenario models to test assumptions and evaluate alternative planning outcomes.
• o Machine Learning: Foundational to intermediate experience with ML frameworks and methodologies (scikit-learn, XGBoost, or similar).
• o Model Evaluation: Understanding of model validation metrics (R², MAE, RMSE, cross-validation, custom scoring functions).
• o SQL: Proficiency in querying, joining tables, data manipulation, and interpreting complex queries.
• o Statistical Analysis: Understanding of statistical modeling, hypothesis testing, and experimental design.
• o Data Exploration: Ability to independently explore enterprise datasets and identify patterns, gaps, and opportunities.
• o Data Cleaning: Experience handling messy data, identifying inconsistencies, and standardizing formats across heterogeneous systems.
• o Data Integration: Experience merging multiple datasets from various enterprise data sources (SAP, Salesforce, Databricks, ERP/CRM).
• o Anomaly Detection: Sharp eye for finding outliers, errors, and unusual patterns in structured and unstructured data.
• o Semantic Data Models: Understanding of data modeling concepts across heterogeneous systems.
• o Forecasting & Prediction: Experience developing models for scenario modeling and predictive use cases.
• o Large Language Models (LLMs): Familiarity with LLMs and basic prompt engineering techniques for practical business applications.
• o Reverse Engineering: Ability to review existing dashboards, ML models, and reports to understand design patterns, business requirements, and underlying data sources
• o SQL Query Analysis: Strong capability to read and interpret complex SQL queries to understand data flows and business logic
• o Data Source Understanding: Skills to trace data lineage, review prepared data sources, and comprehend underlying data structures
• o Pipeline Collaboration: Experience working with Data Engineers to ensure data requirements are correctly implemented at pipeline and infrastructure level

Nice to Have Skills

• Advanced ML/Deep Learning: Experience with TensorFlow, PyTorch, neural networks, or deep learning applications.
• Unit Testing: pytest or similar frameworks for data science code quality.
• Experience with P6 (Primavera), MS Project, or similar project execution systems.
• MLOps: Model versioning, experiment tracking (MLflow, Weights & Biases), deployment basics.
• Cloud Platforms: Familiarity with Azure, AWS, or GCP for data science workflows.
• Advanced LLM Applications: Experience with fine-tuning, RAG (Retrieval-Augmented Generation), or agent frameworks.
• Data Governance: Understanding of data governance principles and responsible AI practices.
• Enterprise Systems: First-hand experience with SAP, Salesforce, Databricks, or similar ERP/CRM systems from a data consumption perspective.

Key Responsibilities

• o Data Analysis & Intelligence
  • o Analyze quality data