Responsibilities
A client with Kforce is seeking a Data Scientist to join their team in Orlando, FL. Summary: In this role, the Data Scientist will design, implement, and maintain advanced data pipelines and analytical frameworks that feed into cutting-edge AI models. They will collaborate with machine learning engineers, AI architects, and domain experts to ensure datasets are high-quality, well-structured, and optimized for model training and deployment. By transforming raw data into actionable insights, the Data Scientist will be a crucial enabler of scalable, reliable AI solutions for real-world energy applications. Data Engineering:
- Design, build, and optimize scalable data pipelines for acquiring and processing large, complex datasets (e.g., IoT sensors, 2D/3D imaging)
- Implement and manage ETL (Extract, Transform, Load) processes to prepare data for AI model training
- Monitor and maintain data integrity, quality, and accessibility throughout the AI development lifecycle
- Develop and enforce standards for data governance, storage, and security
Data Science
- Perform exploratory data analysis (EDA) to identify trends, anomalies, and patterns relevant to AI objectives
- Conduct data preprocessing, feature engineering, and labeling to create machine learning-ready datasets
- Collaborate with machine learning engineers to inform model architecture choices and training strategies
- Validate AI models by applying advanced statistical analysis and performance evaluation metrics
Collaboration & Integration:
- Partner with multidisciplinary teams to integrate trained AI models into operational systems
- Ensure data workflows and model pipelines are reusable, flexible, and well documented for future development cycles
- Support iterative improvement processes by analyzing model performance and adjusting data inputs accordingly
Requirements
- Bachelor's or Master's degree in Computer Science, Data Science, Engineering, Mathematics, or a related field
- Proven experience in data engineering and/or data science, preferably with large-scale sensor or geospatial data
- Proficiency in Python, SQL, and ML frameworks such as TensorFlow or PyTorch
- Familiarity with 2D/3D data formats, point cloud processing, and GIS tools is a strong plus
- Solid understanding of machine learning concepts and experience supporting AI/ML model development
- Strong analytical and problem-solving skills, with attention to detail and data quality
- Excellent communication skills in English (spoken and written); German is a plus
- Ability to work independently and collaboratively in a fast-paced, agile environment
Preferred Qualifications
- Experience with DevOps, CI/CD pipelines, and containerization (Docker, Kubernetes)
- Knowledge of MLOps practices and model deployment in production environments
- Familiarity with scientific literature and research best practices
The pay range is the lowest to highest compensation we reasonably in good faith believe we would pay at posting for this role. We may ultimately pay more or less than this range. Employee pay is based on factors like relevant education, qualifications, certifications, experience, skills, seniority, location, performance, union contract and business needs. This range may be modified in the future.
We offer comprehensive benefits including medical/dental/vision insurance, HSA, FSA, 401(k), and life, disability & ADD insurance to eligible employees. Salaried personnel receive paid time off. Hourly employees are not eligible for paid time off unless required by law. Hourly employees on a Service Contract Act project are eligible for paid sick leave.
Note: Pay is not considered compensation until it is earned, vested and determinable. The amount and availability of any compensation remains in Kforce's sole discretion unless and until paid and may be modified in its discretion consistent with the law.
This job is not eligible for bonuses, incentives or commissions.
Kforce is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, pregnancy, sexual orientation, gender identity, national origin, age, protected veteran status, or disability status.
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