Data Scientist

This is a fully remote position, open to applicants in United States, +1 more country.

📋 Description

• Gather, clean, process, and analyze extensive datasets from various sources.

• Conduct exploratory data analysis to uncover distributions, relationships, trends, and business opportunities.

• Design, train, test, and assess machine learning models.

• Utilize statistical techniques and mathematical methods to back evidence-based decisions.

• Write efficient Python code leveraging Pandas, NumPy, Scikit-learn, and Matplotlib.

• Develop predictive, classification, regression, clustering, and other machine learning solutions.

• Employ SQL databases for extracting, manipulating, and analyzing structured data.

• Create data visualizations, reports, and presentations that convey analytical insights.

• Assess model performance and suggest enhancements.

• Collaborate with software engineers, data analysts, and cross-functional teams to transform business requirements into analytical solutions.

• Support data processing and machine learning workflows.

• Maintain thorough documentation of datasets, methodologies, experiments, and model outcomes.

• Keep abreast of developments in data science techniques, machine learning technologies, and industry best practices.

⛳️ Requirements

• Master's degree in Data Science, Computer Science, Statistics, Mathematics, Artificial Intelligence, Machine Learning, or a related technical discipline.

• 0–1 year of experience in Data Science, Machine Learning, Data Analytics, or a related technical position.

• Strong programming expertise in Python and knowledge of Pandas, NumPy, and Scikit-learn.

• Solid grasp of statistics, probability, linear algebra, and mathematical principles.

• Familiarity with both supervised and unsupervised learning methodologies.

• Understanding of data preprocessing, cleaning, feature engineering, and exploratory data analysis.

• Proficient in SQL for querying, joining, filtering, and analyzing datasets.

• Knowledge of Matplotlib, Seaborn, or Plotly.

• Understanding of regression, decision trees, random forests, clustering, and classification techniques.

• Familiarity with Jupyter Notebook, Google Colab, or similar development environments.

• Basic understanding of model evaluation, validation methods, and performance metrics.

• Familiarity with Git and GitHub for version control and collaborative development.

• Strong analytical thinking, critical reasoning, and problem-solving skills.

• Ability to interpret complex data and effectively communicate findings.

• High attention to detail, teamwork, and eagerness to learn new technologies.

• Preferred: experience with academic projects, internships, or personal projects in data science, machine learning, or predictive analytics.

• Preferred: familiarity with TensorFlow or PyTorch.

• Preferred: basic understanding of NLP and generative AI concepts.

• Preferred: exposure to AWS, Microsoft Azure, or Google Cloud Platform.

• Preferred: familiarity with model deployment, APIs, or machine learning pipelines.

• Preferred: experience in participating in data science competitions or working with real-world datasets.

🏝️ Benefits

• Opportunity to contribute to an innovative, AI-driven technology company.

• Hands-on experience with real-world data science and machine learning projects.

• Opportunities to enhance programming, statistical analysis, and machine learning skills.

• Collaborative atmosphere that promotes experimentation, innovation, and ongoing learning.

• Opportunities for professional development and growth in technical careers.

• Exposure to contemporary data science tools, technologies, and analytical workflows.

• Chance to contribute to data-driven solutions and impactful business initiatives.