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Abacus Service Corporation · 3 hours ago

Data Science & Machine Learning Engineer

Juno Beach, FL

Contract

Onsite

Senior Level

5+ years exp

Abacus Service Corporation is focused on Data Science and Analytics for Power Commodity Trading, and they are seeking a Data Science & Machine Learning Engineer. The role involves developing machine learning models and analytics systems, with a strong emphasis on power market dynamics and advanced analytics.

Health CareInformation Technology

Growth Opportunities

H1B Sponsor Likely

Hiring Manager

Vikram Pitla

Responsibilities

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)

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

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

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

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

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

Qualification

PythonMachine LearningData ScienceSQLAWSStatisticsTime Series ModelingData VisualizationData GovernanceCommunication Skills

Required

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, power, or commodities markets

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