> Markdown version of [/jobs/ext/165454-data-scientist-python-developer](https://www.wearedevelopers.com/jobs/ext/165454-data-scientist-python-developer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Scientist (Python Developer) - **Company:** UST Global Inc - **Location:** United States - **Experience:** Starter - **Salary:** $56,000.0 - $84,000.0 - **Contract:** Temporary contract - **Skills:** Amazon Web Services, Data Analysis, Microsoft Azure, Cloud Computing, Code Review, Data Cleansing, Information Engineering, Data Visualization, Python (Programming Language), Machine Learning, NumPy, SQL Databases, Jupyter Notebook, Data Processing, Google Cloud, Feature Engineering, Git, Usage Tracking, Pandas, Matplotlib, Scikit Learn, Information Technology, Data Analytics, Data Management, Software Version Control, Data Pipelines, Unsupervised Learning - **Published:** May 19, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=6b0a320fa658dc25 ## About the Role * Strong foundational knowledge of Python for data analysis and development * Familiarity with Python libraries such as Pandas, NumPy, Matplotlib/ Seaborn, Scikit-learn * Understanding of basic statistics, probability, and data analysis concepts * Exposure to data wrangling, exploratory data analysis (EDA), and data visualization * Basic understanding of machine learning concepts (supervised and unsupervised learning) * Technical Skills (Good to Have) * Exposure to Jupyter Notebooks or similar analytical environments * Familiarity with SQL or basic database querying concepts * Awareness of cloud-based analytics or data platforms (AWS, Azure, GCP - conceptual level) * Exposure to version control systems such as Git * Basic knowledge of data pipelines or data engineering concepts * Educational Qualifications * Bachelor's degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related quantitative field * Relevant academic projects, internships, or certifications in data science or analytics are a plus * Experience * 0-2 years of experience in data science, analytics, or related roles * Entry-level candidates, recent graduates, or early-career professionals are encouraged to apply * Behavioral & Professional Competencies * Strong analytical and problem-solving mindset * Willingness to learn and adapt in a fast-paced, collaborative environment * Good verbal and written communication skills * Ability to work effectively as part of a team under guidance and direction * Attention to detail and commitment to quality deliverables., data science,python,numpy,scikit-learn,data wrangling,exploratory data analysis,data visualization ## Description The Data Scientist (Entry Level) will work as a team member on managed outcome- and capacity-based data analytics and data science initiatives, including projects, Proof of Concepts (POCs), and Minimum Viable Products (MVPs). The opportunity: * Data Science & Analytics Delivery * Participate as a team member in data analytics and data science projects, including managed outcome and capacity-based engagements. * Support the development and execution of POCs and MVPs to validate analytical approaches, models, and hypotheses. * Assist in translating business and scientific problems into data-driven analytical solutions under supervision. * Perform data exploration, data preparation, and feature engineering to support analytics and modeling activities. * Development & Implementation * Develop and maintain analytical scripts, models, and workflows using Python and relevant data science libraries. Implement statistical, machine learning, or analytical techniques as guided by senior data scientists or architects. * Support model testing, validation, and refinement to ensure accuracy and reliability of outputs. Contribute to code reviews, documentation, and version-controlled development practices. * Collaboration & Stakeholder Support * Work closely with senior data scientists, data engineers, and crossfunctional delivery teams. * Participate in team discussions, sprint ceremonies, and knowledgesharing sessions. Support communication of analytical findings through clear documentation, visualizations, and presentations as needed. * Learning & Continuous Improvement * Learn and apply industry best practices in data science, analytics, and responsible data usage. Stay current with emerging tools, frameworks, and techniques relevant to data science and analytics. Actively seek feedback and mentorship to improve technical and professional capabilities. This position description identifies the responsibilities and tasks typically associated with the performance of the position. 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