Hiring: W2 Candidates Only
Visa: Open to any visa type with valid work authorization in the USA
Job Description:
A Data Scientist analyzes complex datasets to uncover insights identify trends and help organizations make data-driven decisions. They use statistical analysis machine learning and data visualization to solve real-world business problems. Data Scientists work at the intersection of technology business and mathematics turning raw data into actionable intelligence.
Key Responsibilities:
Data Collection & Cleaning:
Gather preprocess and clean large datasets from various sources to ensure data quality and consistency.
Exploratory Data Analysis (EDA):
Analyze data patterns and relationships to understand underlying trends.
Use tools like Python (Pandas NumPy) R or SQL for analysis.
Statistical Modeling & Machine Learning:
Build predictive and classification models using algorithms such as regression decision trees random forests and neural networks.
Work with machine learning frameworks like Scikit-learn TensorFlow or PyTorch.
Data Visualization & Reporting:
Communicate findings effectively using visualization tools such as Tableau Power BI Matplotlib or Seaborn.
Prepare dashboards and reports for management and business teams.
Business Problem Solving:
Collaborate with stakeholders to define problems and develop data-driven solutions.
Translate business requirements into technical data models.
Big Data & Cloud Computing:
Work with large datasets using Spark Hadoop or cloud platforms (AWS GCP Azure).
Research & Continuous Improvement:
Stay updated with new technologies algorithms and trends in AI and data science.
Required Skills:
Proficiency in Python or R for data analysis
Strong command of SQL and database querying
Knowledge of machine learning algorithms and data modeling
Experience with data visualization tools (Tableau Power BI Matplotlib Seaborn)
Understanding of statistics probability and hypothesis testing
Familiarity with big data technologies (Hadoop Spark)
Strong analytical thinking and problem-solving ability
Good communication and storytelling skills for presenting insights
Hiring: W2 Candidates OnlyVisa: Open to any visa type with valid work authorization in the USA Job Description: A Data Scientist analyzes complex datasets to uncover insights identify trends and help organizations make data-driven decisions. They use statistical analysis machine learning and data vi...
Hiring: W2 Candidates Only
Visa: Open to any visa type with valid work authorization in the USA
Job Description:
A Data Scientist analyzes complex datasets to uncover insights identify trends and help organizations make data-driven decisions. They use statistical analysis machine learning and data visualization to solve real-world business problems. Data Scientists work at the intersection of technology business and mathematics turning raw data into actionable intelligence.
Key Responsibilities:
Data Collection & Cleaning:
Gather preprocess and clean large datasets from various sources to ensure data quality and consistency.
Exploratory Data Analysis (EDA):
Analyze data patterns and relationships to understand underlying trends.
Use tools like Python (Pandas NumPy) R or SQL for analysis.
Statistical Modeling & Machine Learning:
Build predictive and classification models using algorithms such as regression decision trees random forests and neural networks.
Work with machine learning frameworks like Scikit-learn TensorFlow or PyTorch.
Data Visualization & Reporting:
Communicate findings effectively using visualization tools such as Tableau Power BI Matplotlib or Seaborn.
Prepare dashboards and reports for management and business teams.
Business Problem Solving:
Collaborate with stakeholders to define problems and develop data-driven solutions.
Translate business requirements into technical data models.
Big Data & Cloud Computing:
Work with large datasets using Spark Hadoop or cloud platforms (AWS GCP Azure).
Research & Continuous Improvement:
Stay updated with new technologies algorithms and trends in AI and data science.
Required Skills:
Proficiency in Python or R for data analysis
Strong command of SQL and database querying
Knowledge of machine learning algorithms and data modeling
Experience with data visualization tools (Tableau Power BI Matplotlib Seaborn)
Understanding of statistics probability and hypothesis testing
Familiarity with big data technologies (Hadoop Spark)
Strong analytical thinking and problem-solving ability
Good communication and storytelling skills for presenting insights
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