GARGI TECHNOLOGIES INC logo

Data Analyst

Pennsburg, PA, PA permanent 3 days ago IT
Salary & Market Data
Matched to BLS occupational data · Pennsylvania

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.

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