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Data Analyst

Job

GARGI TECHNOLOGIES INC

Pennsburg, PA (In Person)

Full-Time

Posted 1 week ago (Updated 1 week ago) • Actively hiring

Expires 7/15/2026

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Job Description

Data Scientist | Full-Time 🚀
We''re Hiring:
Data Scientist Are you passionate about turning data into actionable insights? We are looking for a Data Scientist who can leverage advanced analytics, machine learning, and statistical modeling to solve complex business problems and drive data-driven decision-making. ## Key Responsibilities
  • Analyze large and complex datasets to identify trends, patterns, and business opportunities.
  • Build, validate, and deploy machine learning models for predictive and prescriptive analytics.
  • Develop data pipelines and workflows to support data collection, processing, and reporting.
  • Collaborate with cross-functional teams including engineering, product, and business stakeholders.
  • Create dashboards, visualizations, and reports to communicate findings effectively.
  • Perform exploratory data analysis (EDA) and feature engineering.
  • Monitor model performance and recommend improvements as needed. ## Required Skills & Qualifications
  • Bachelor''s or Master''s degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, or a related field.
  • 2+ years of experience in Data Science, Machine Learning, or Analytics roles.
  • Strong proficiency in Python and SQL.
  • Experience with Machine Learning frameworks such as Scikit-learn, TensorFlow, PyTorch, or XGBoost.
  • Solid understanding of statistics, probability, hypothesis testing, and predictive modeling.
  • Experience working with data visualization tools such as Tableau, Power BI, or Looker.
  • Knowledge of cloud platforms such as AWS, Azure, or Google Cloud Platform (Google Cloud Platform).
  • Experience handling structured and unstructured datasets. ## Preferred Qualifications
  • Experience with NLP, Deep Learning, Computer Vision, or Generative AI projects.
  • Familiarity with big data technologies such as Spark, Hadoop, or Databricks.
  • Experience deploying machine learning models in production environments.
  • Knowledge of MLOps practices and tools.