Principal Data Scientist

Job: Principal Data Scientist Location: Vero Beach, Florida Duration : 1 Year We are seeking a Data Scientist with 9 or more years of hands-on experience in data cleaning, transformation, and analysis using Python. The ideal candidate is comfortable working with large, messy datasets, has exposure to modern data technologies, and brings a strong analytical mindset. Experience with machine learning and LLMs is a strong plus. • Data scientists with proven time-series forecasting portfolios • Candidates from energy, utility, or renewable sectors • Profiles showing ARIMA/SARIMAX/Prophet/LSTM experience • Evidence of weather-dependent forecasting projects • Production deployment of operational forecasting systems 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 to extract and prepare data 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 where applicable Experiment with and support LLM based solutions (prompting, embeddings, APIs) as needed Ensure data quality, reliability, and documentation Required Skills & Qualifications 9+ years of experience as a Data Scientist / Data Analyst Strong proficiency in Python for data manipulation and analysisPandas, NumPy, SciPy Solid understanding of data cleaning, transformation, and feature engineering Experience with SQL (PostgreSQL, MySQL, BigQuery, Snowflake, etc.) Familiarity with data visualization toolsMatplotlib, Seaborn, Plotly, or Power BI/Tableau Understanding of statistics and data analysis fundamentals Experience working with APIs and external data sources Strong problem solving and communication skills Modern / Latest Tech Stack (Preferred) Python (3.x) Pandas, NumPy, Scikit learn Jupyter, VS Code Git / GitHub Cloud platforms: AWS / Azure / GCP Data tools: Airflow, dbt, Spark (basic exposure) Containerization: Docker (nice to have) Good to Have Hands on experience with Machine Learning modelsRegression, classification, clustering, time series Exposure to LLMs and Generative AIOpenAI / Azure OpenAI APIs Prompt engineering Embeddings, vector databases (FAISS, Pinecone, Chroma) Experience with NLP or text analytics Knowledge of MLOps basics (model versioning, monitoring)