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Principal Programmer Analyst - Data Scientist

Principal Programmer Analyst - Data Scientist

VDart IncFL, United States
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Job Title : PrincipalIT Programmer Analyst - Data Scientist

Location : Juno Beach, FL

Description :

  • Responsible for the development and integration of new or existing applications into the technical infrastructure and existing business processes.
  • Provides technical or functional guidance to project or work teams as needed within a specific discipline.
  • Collaborates on an on-going basis with the Business Systems Analyst. Analyzes, designs, develops, tests, debugs, implements, maintains and / or enhances existing or new systems that are reliable and efficient.

Requirements Checklist :

  • Data Science & Analytics & Machine Learning for Power Marketing
  • Focus is on the Data Science

    • 1. Core Qualifications

  • Master's or PhD in Data Science, Computer Science, Finance, Engineering, or Applied Mathematics
  • 5+ years of experience in machine learning or advanced analytics, with at least 2 years in energy market applications
  • Proficiency in Python (pandas, NumPy, scikit-learn, PyTorch, TensorFlow) and SQL
  • Experience deploying production-grade ML and analytics systems in AWS, Azure, or GCP
  • Strong foundation in statistics, linear algebra, and optimization

    • 2. Machine Learning & AI Expertise

  • Experience with supervised, unsupervised, and reinforcement learning for market forecasting or optimization
  • Proficient in LLMs (GPT, Llama, Mistral) and RAG (Retrieval-Augmented Generation) pipelines for automating report generation, trade rationale summaries, or market insights
  • Hands-on experience fine-tuning or evaluating generative models for quantitative or text-based analytics
  • Familiarity with agentic AI frameworks (LangChain, LlamaIndex, CrewAI) for autonomous data gathering, analysis, and decision support
  • Strong understanding of feature engineering, model interpretability, and bias control

    • 3. Agentic & Autonomous Decision Systems

  • Experience creating intelligent trading assistants or agent frameworks that monitor, forecast, and act based on real-time data
  • Familiarity with planning, memory, and multi-agent collaboration concepts
  • Implementation of guardrails and ethical constraints in autonomous AI systems

    • 4. Forecasting & Quantitative Modeling

  • Time series modeling (ARIMA, Prophet, LSTM, XGBoost) for price, load, or renewable generation forecasting
  • Optimization and scenario modeling for trading positions, hedges, or dispatch strategies
  • Proficiency with stochastic modeling, Monte Carlo simulations, and VaR analysis
  • Ability to integrate weather data, grid conditions, and market signals into predictive systems

    • 5. Data Infrastructure & Engineering

  • Strong data architecture skills : ETL / ELT pipelines, dbt, Airflow, or Prefect
  • Experience with data warehouses (DataBricks, Snowflake)
  • Familiarity with vector databases (FAISS, Pinecone, Weaviate) for retrieval-augmented analytics
  • Data governance awareness : versioning, lineage, security, and compliance

    • 6. Analytics, Visualization & Communication

  • Strong experience with dashboards and visualization tools (Power BI, Tableau, Plotly)
  • Ability to design KPIs and visual analytics for trading performance, market exposure, and forecast accuracy
  • Experience building automated insight pipelines or LLM-based analytics assistants
  • Skilled in translating technical findings into clear narratives for traders and executives

    • 7. Statistical & Mathematical Rigor

  • Advanced modeling in regression, classification, and optimization
  • Ability to quantify uncertainty, correlation, and elasticity across commodities
  • Understanding of volatility clustering and non-linear time dependencies

    • 8. Soft Skills

  • Clear communication of analytical results to both technical and business stakeholders
  • Operates effectively in time-sensitive, high-stakes environments
  • Scientific rigor in documentation and model validation
  • Balance of innovation (AI-driven) and practicality (trader needs)

    • 9. Bonus / Differentiators

  • Domain Expertise Power & Commodities :
  • Understanding of power market dynamics (generation, transmission, demand forecasting, ISO / RTO markets such as PJM, ERCOT, MISO, CAISO)
  • Familiarity with trading instruments : DA / RT markets, FTRs, CRRs, PPAs, futures, and swaps
  • Knowledge of natural gas, renewables, and carbon markets
  • Experience modeling locational marginal prices (LMP), congestion, and portfolio risk
  • Understanding of regulatory and compliance data (FERC, EIA, ISO market data)
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