Actively looking for a Data Scientist

Job Title: Principal Data Scientist Location: Juno Beach, FL onsite day 1(Need Only Local consultants) Mandatory skills ARIMA/SARIMAX/Prophet/LSTM models Domain & Advanced Expectations: Experience working with large, messy datasets and modern data technologies Strong analytical mindset with ML and LLM exposure as a plus Proven time-series forecasting experience Candidates from energy, utility, or renewable sectors preferred Experience with ARIMA/SARIMAX/Prophet/LSTM models Evidence of weather-dependent forecasting projects Experience deploying production-grade forecasting systems Required Skills & Qualifications: 9+ years of experience as a Data Scientist / Data Analyst Strong proficiency in Python for data manipulation and analysis (Pandas, NumPy, SciPy) Solid understanding of data cleaning, transformation, and feature engineering Experience with SQL (PostgreSQL, MySQL, BigQuery, Snowflake, etc.) Familiarity with data visualization tools (Matplotlib, Seaborn, Plotly, Power BI/Tableau) Strong understanding of statistics and data analysis fundamentals Experience working with APIs and external data sources Strong problem-solving and communication skills Key Responsibilities: Clean, preprocess, and transform structured and unstructured data using Python Perform exploratory data analysis (EDA) to uncover insights and trends Build reusable data pipelines and feature engineering workflows Work with SQL and/or cloud-based data warehouses for data extraction and preparation Collaborate with stakeholders to translate business problems into data-driven solutions Develop and maintain analytical models and dashboards Apply basic to intermediate machine learning techniques as required Experiment with and support LLM-based solutions (prompting, embeddings, APIs) Ensure data quality, reliability, and proper documentation Modern / Latest Tech Stack (Preferred): Python (3.x) Pandas, NumPy, Scikit-learn Jupyter, VS Code Git / GitHub Cloud platforms: AWS / Azure / Google Cloud Platform Data tools: Airflow, dbt, Spark (basic exposure) Containerization: Docker (nice to have) Good to Have: Hands-on experience with Machine Learning models: regression, classification, clustering, time series Exposure to LLMs and Generative AI (OpenAI / Azure OpenAI APIs) Prompt engineering Embeddings and vector databases (FAISS, Pinecone, Chroma) Experience with NLP or text analytics Knowledge of MLOps basics (model versioning, monitoring)