SPECTRAFORCE TECHNOLOGIES Inc.
Data Scientist
Newark, New Jersey, USA · Contract
Sponsorship not specifiedDetected 75 days ago
PythonSQLAWSAzureCI/CDJenkinsMachine LearningData AnalysisData ScienceData VisualizationLLMsRAGAgentic AILangGraphStatisticsA/B TestingStakeholder ManagementTest AutomationLeadershipCommunicationCollaborationProblem Solving
About the role
- Job Title: Data Scientist Duration: 12 months Location: Hybrid (Newark, NJ) and requires your on-site presence on a reoccurring weekly basis as determined by your business.
- Your manager will provide additional details relative to the specific number of days you are expected to be on-site.
- Here is what you can expect in a typical day: Provide deep technical leadership to a portfolio of high impact data science initiatives involving sales and advisor experience.
Requirements
- Identify the optimal sets of data, models, training, and testing techniques required for successful product delivery.
- Remove complex technical impediments Leverage your experience and skills to identify new opportunities where data science and AI can improve experiences, gain efficiencies, and generate sales.
- Apply hands-on experience to ensuring best-in-class model development.
- Familiarity with Python, SQL, AWS, and JIRA.
- Familiarity with LLMs, deployment of LLMs, RAG, LangChain, LangGraph, and Agentic AI concepts.
- Knowledge of how databases are structured and function in order use them efficiently.
Skills
- Applied Statistics, Computer Science, or Engineering or experience in related fields with a focus on machine learning, AI, and LLMs.
- Experience with agile development methodologies, Test-Driven Development (TDD), and product management.
- Experience and/or deep expertise with several of the following:
Benefits
- Understanding of machine learning theory, including the mathematics underlying machine learning algorithms.
- Expertise in the application of machine learning theory to building, training, testing, interpreting and monitoring machine learning models.
- Expertise in traditional machine learning models (unsupervised, XGBoost, etc.) and Large Language Models (OpenAI, Claude).
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