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)