Data & Analytics (D&A) Developer II--Job ID: 4005

RISINGSUN TECHNOLOGIES; Greenville (SC); Hybrid; USD 58,000 - 77,000; Full time

Job summary

RISINGSUN TECHNOLOGIES is seeking a Data Scientist to support engineering operations and strategic planning in a hybrid role based in Greenville, SC or Atlanta, GA. The position emphasizes analytics, AI/ML solutions, and forecasting to improve project execution and resource planning.

You will connect business requirements with IT teams, develop dashboards, and contribute to risk identification. Strong Python, SQL, and statistical modeling skills are essential for this role.

Qualifications

• Strong Python proficiency with data libraries and pipelines.
• Advanced SQL skills for complex queries and data manipulation.
• Statistical modeling, hypothesis testing and experimental design.
• Foundational to intermediate ML experience with scikit-learn, XGBoost, or similar.

Responsibilities

• Analyze enterprise data from SAP, Salesforce, Databricks, Power BI, labor, and finance systems to identify patterns and gaps.
• Clean, integrate, and validate large structured and unstructured datasets.
• Develop and validate machine learning models for demand forecasting and planning.
• Build Python ETL pipelines for model training and automated forecasting.

Skills

Python

SQL

Statistical modeling

Machine learning

Forecasting

Data exploration

Data integration

English communication

Prompt engineering (LLMs)

Job description

Data & Analytics (D&A) Developer II--Job ID: 4005

We're Hiring: Data Scientist – Engineering Operations & Strategy

Location: Greenville, SC, or Atlanta, GA

Working Model: Hybrid

Travel: No

Bill Rate: $49/hr

Contract Duration: Approximately 12 Months (Possible extension)

Hours: 40 hours/week

We're seeking an analytical, collaborative Data Scientist to support engineering operations, business planning, and program reporting. You'll connect business and engineering requirements with data and IT teams, developing analytics and AI/ML solutions that improve forecasting, resource planning, and project execution.

Key Responsibilities

• Analyze enterprise data from SAP, Salesforce, Databricks, Power BI, labor, and finance systems to identify patterns, gaps, and improvement opportunities.


• Clean, integrate, and validate structured and unstructured datasets, including datasets exceeding 100,000 rows.


• Develop and validate machine learning models for demand forecasting, scenario planning, and predictive analytics.


• Build and maintain Python pipelines for ETL, model training, and automated forecasting.


• Create what-if models to evaluate demand, resource capacity, costs, and alternative planning outcomes.


• Track project performance through Primavera P6 and other enterprise systems; analyze variances in hours, budgets, and timelines.


• Support executive dashboards, KPI reporting, and early identification of project risks.


• Review existing dashboards, SQL queries, semantic models, and data pipelines to improve reporting and modeling assets.


• Apply LLMs and prompt engineering to support decision-making and workflow automation.


• Document models, data definitions, and findings; communicate insights, progress, risks, and dependencies to stakeholders.

Must-Have Skills

• Strong Python proficiency: pandas, NumPy, scikit-learn, SciPy, curve fitting, and object-oriented programming.


• Strong SQL skills, including complex query interpretation, joins, and data manipulation.


• Statistical modeling, hypothesis testing, and experimental design.


• Foundational to intermediate machine learning experience using scikit-learn, XGBoost, or similar tools.


• Model evaluation using R², MAE, RMSE, cross-validation, and custom scoring functions.


• Scenario planning, forecasting, and what-if analysis.


• Data exploration, cleaning, integration, anomaly detection, and data lineage analysis.


• Understanding of semantic data models and heterogeneous enterprise systems.


• Familiarity with LLMs and basic prompt engineering.


• Ability to interpret existing dashboards, models, and business logic and collaborate with Data Engineers.


• Strong analytical thinking, stakeholder communication, ownership, and learning agility.


• Fluent written and spoken English; ability to collaborate across international teams and time zones.

Nice-to-Have Skills

• TensorFlow, PyTorch, neural networks, or deep learning.


• pytest or similar testing frameworks.


• Primavera P6, MS Project, or similar project execution tools.


• MLOps, MLflow, Weights & Biases, and deployment fundamentals.


• LLM fine-tuning, RAG, or agent frameworks.


• Data governance and responsible AI practices.


• Hands-on enterprise data experience with SAP, Salesforce, or Databricks.