What are the responsibilities and job description for the Data Scientist position at Mergen IT LLC?
Job Title: Data Scientist
Location : Austin, TX (Day One Onsite to Client Location)
H-1B transfers are accepted.
Job Description
We are seeking a Data Scientist with 6 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.
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
• 3 years of experience as a Data Scientist / Data Analyst
• Strong proficiency in Python for data manipulation and analysis
o 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
o Matplotlib, 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 / 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
o Regression, classification, clustering, time series
• Exposure to LLMs and Generative AI
o OpenAI / Azure OpenAI APIs
o Prompt engineering
o Embeddings, vector databases (FAISS, Pinecone, Chroma)
• Experience with NLP or text analytics
• Knowledge of MLOps basics (model versioning, monitoring)