Data Scientist
The Data & Analytics Developer II at Confidential Client is a contract role focused on leveraging AI, machine learning, and advanced analytics to drive data-driven decision-making in the energy sector. This hybrid position involves developing predictive models, managing enterprise data pipelines, and collaborating with data engineering teams to solve complex business challenges using cutting-edge technologies including large language models and cloud platforms.
About Careertakes
👉 Important disclosure: Careertakes is a third-party recruiting platform supporting this hiring process. If selected, you will be employed directly by our client, Manufacturing.
Applicants for this role may also receive access to additional matched opportunities through the Careertakes platform.
What You’ll Do
This is an associate-level Data Scientist role supporting a confidential client’s analytics and engineering teams. You will:
- Develop, validate, and deliver machine learning and predictive models using Python (Pandas, NumPy, scikit-learn)
- Design and maintain data cleaning, integration, and quality checks for enterprise data sources (SAP, Salesforce, Databricks, ERP/CRM)
- Build and support data pipelines and collaborate closely with data engineering to move models toward production
- Perform statistical analysis, scenario planning, and forecasting to inform business decisions
- Apply Large Language Models (LLMs) and prompt engineering for analytics, automation, and RAG-style solutions
- Translate business requirements into technical solutions and communicate results to stakeholders
- Document models, assumptions, and runbooks for reuse and auditability
Key Qualifications
- Associate-level experience in data science, analytics, or closely related roles
- Strong Python skills (Pandas, NumPy, scikit-learn)
- Proficiency with SQL and applied statistical analysis
- Hands-on experience with machine learning & predictive modeling workflows
- Experience with data cleaning, integration, and enterprise data sources (SAP, Salesforce, Databricks, ERP/CRM)
- Familiarity working on or alongside data pipelines and data engineering teams
- Practical exposure to LLMs or prompt-engineering approaches
- Strong analytical and communication skills; able to present findings to technical and non-technical stakeholders
- Bachelor’s degree in a quantitative field or equivalent experience
Nice to Have
- Experience with Azure, AWS, or GCP
- Deep learning frameworks (TensorFlow or PyTorch)
- MLflow, MLOps, or related production ML tooling
- Scheduling / planning tools (Primavera P6 or MS Project)
- Experience with Retrieval-Augmented Generation (RAG) and advanced LLM applications
Logistics & Compensation
- Location: Greenville, SC (Hybrid)
- Employment type: Full-time (12-month engagement)
- Schedule: 40 hours/week
- Pay rate: $55.20 / hour (W-2, without benefits)
- You will be employed directly by our client (the confidential client) if selected.
Why Join
This role offers the chance to apply modern ML and LLM techniques against large enterprise data sets in a manufacturing environment. You’ll work cross-functionally with data engineers and business stakeholders to deliver models that influence real operational decisions.
Equal Opportunity & Hiring Transparency
Careertakes and our client are Equal Opportunity Employers committed to building a diverse and inclusive workforce. We prohibit discrimination or harassment of any kind. To support a fair and efficient hiring process, AI tools may be used to assist with application review or resume screening. These tools do not replace human decision-making. Final hiring decisions are made by people.
If you have questions about how your data is used, please contact us directly.
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