Data Scientist

Data Scientist
Location: United States
Job Type: Full-Time
Work Arrangement: Remote / Hybrid
Experience Level: Entry-Level / Associate
Job Overview
We are seeking a motivated and analytical Data Scientist to help transform business data into meaningful insights and practical solutions. This role will support data analysis, statistical modeling, machine learning, experimentation, and data visualization to help teams make informed decisions.
The ideal candidate has a strong foundation in statistics, programming, and data analysis, along with an interest in solving business problems through data. This position is suitable for candidates with academic projects, internships, research experience, or early professional experience in data science, analytics, mathematics, statistics, or computer science.
Key Responsibilities
Collect, clean, and prepare structured and unstructured data for analysis.
Analyze large datasets to identify trends, patterns, and relationships.
Develop statistical models and machine learning solutions for business problems.
Perform exploratory data analysis and communicate key findings.
Build and evaluate predictive models using appropriate techniques.
Create data visualizations, dashboards, and reports to communicate insights.
Use Python, SQL, and other analytical tools to process and analyze data.
Work with cross-functional teams to understand business and analytical requirements.
Design and analyze experiments and A/B tests when applicable.
Evaluate model performance and identify opportunities for improvement.
Document analytical methodologies, assumptions, findings, and results.
Assist with feature engineering, model validation, and data preparation.
Monitor data quality and identify potential data issues.
Translate analytical findings into clear business recommendations and presentations.
Support the development and improvement of data pipelines and analytical workflows.
Research new data-science techniques, tools, and technologies.
Contribute to data science projects from initial analysis through implementation.
Qualifications
Bachelor's degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, or a related field preferred.
Master's degree is a plus but not required for entry-level candidates.
Strong foundation in statistics, probability, and data analysis.
Proficiency in Python or a similar programming language.
Working knowledge of SQL and relational databases.
Familiarity with common data-science and machine-learning concepts.
Strong analytical and problem-solving skills.
Ability to work with large datasets and identify meaningful patterns.
Good communication and presentation skills.
Strong attention to detail and data accuracy.
Ability to work independently and collaborate with cross-functional teams.
Must be legally authorized to work in the United States.
Preferred Qualifications
Experience with pandas, NumPy, scikit-learn, or similar Python libraries.
Familiarity with machine-learning algorithms and model evaluation.
Experience with Tableau, Power BI, or other visualization platforms.
Knowledge of cloud data platforms such as AWS, Azure, or Google Cloud.
Familiarity with Jupyter Notebook and Git.
Experience with data warehousing or ETL processes.
Academic, internship, research, or personal data-science projects.
Portfolio or GitHub projects demonstrating analytical or machine-learning work.

Work arrangement
Yes