Job description

Role: Data Scientist (with prior Data Engineering experience) Location: Charlotte, NC (Onsite In-person Client Interview Required) Duration: Long Term Contract Visa : , , -ead , L2-ead Job Description We are seeking a Data Scientist with around 1 year of hands-on data science experience and a strong background in data engineering to join our client's analytics team in Charlotte, NC. The ideal candidate should possess a solid understanding of data pipelines, data modeling, and machine learning techniques, with the ability to translate business problems into actionable analytical solutions. Key Responsibilities • Develop and deploy machine learning and statistical models to solve business problems and deliver insights. • Work on data preparation, feature engineering, and model training using structured and unstructured data. • Utilize NLP (Natural Language Processing) techniques for text data analysis and insights extraction. • Leverage prior data engineering experience to build efficient data pipelines and ensure data availability for analytics. • Collaborate with cross-functional teams to define data requirements and analytical goals. • Use Python, SQL, and visualization tools to communicate findings effectively. • Evaluate model performance, fine-tune algorithms, and deploy models in production environments. Required Skills & Experience • 1+ year of experience as a Data Scientist (professional). • Previous 4-5 years of experience as a Data Engineer (strong advantage). • Solid understanding of data modeling, ETL processes, and data pipeline development. • Hands-on expertise in Python (Pandas, NumPy, Scikit-learn, PySpark). • Experience with NLP libraries (NLTK, spaCy, Transformers) for text analytics. • Proficiency in SQL and exposure to big data tools like Databricks, Spark, or Airflow. • Knowledge of machine learning techniques such as regression, classification, and clustering. • Familiarity with cloud data environments (AWS, Azure, or Google Cloud Platform). Preferred Skills • Exposure to deep learning frameworks (TensorFlow, PyTorch). • Experience with data visualization tools (Tableau, Power BI, or matplotlib). • Understanding of MLOps concepts and model deployment. • Strong analytical thinking and problem-solving mindset.

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