Data Scientist; Remote

This position is posted by Jobgether on behalf of a partner company. We are currently looking for a Data Scientist in Kentucky (USA) and Massachusetts (USA). This role provides an opportunity to leverage data to generate actionable insights, improve business outcomes, and contribute to data-driven decision-making. You will work with structured and unstructured datasets, building predictive models, performing statistical analyses, and developing dashboards to communicate findings.

The position combines hands‑on technical work with collaboration across analytics, engineering, and business teams, offering exposure to modern data tools, machine learning frameworks, and cloud platforms. Ideal candidates are motivated by problem‑solving, enjoy working with complex data systems, and are eager to see the impact of their work on real‑world projects. Mentorship, technical skill development, and career‑focused guidance are integral to the environment, supporting growth from learning to placement.

• Design, build, and maintain predictive and analytical models using machine learning and statistical techniques
• Perform exploratory data analysis and feature engineering on large, complex datasets
• Develop dashboards, visualizations, and reports to communicate insights to business stakeholders
• Collaborate with data engineers, software developers, and business teams to ensure data quality, integration, and accessibility
• Conduct A/B testing, model validation, and performance monitoring to ensure reliable results
• Document methodologies, assumptions, and workflows to maintain reproducibility and knowledge sharing
• Apply learned skills to real‑world, job‑aligned projects to strengthen both technical expertise and professional experience

• Proficiency in Python, including libraries such as Pandas, Num Py, Scikit‑Learn, and Tensor Flow
• Experience with SQL and relational databases; familiarity with cloud data platforms (AWS, Azure, GCP) is a plus
• Understanding of machine learning concepts, supervised/unsupervised learning, and deep learning techniques
• Knowledge of data visualization tools such as Power BI, Tableau, or similar platforms
• Strong problem‑solving skills, analytical thinking, and ability to translate data into actionable insights
• Ability to collaborate effectively with team members, communicate findings clearly, and document work accurately
• Open to new graduates, career switchers, bootcamp participants, and self‑taught candidates with demonstrable skills

• Experience with NLP, model deployment, A/B testing, or data engineering tools (Spark, Airflow, Databricks)
• Certification in IBM Data Science, AWS Data Analytics, or Microsoft Power BI
• Exposure to statistical inference, KPI reporting, and business impact assessment

• Hands‑on experience working with real‑world data aligned with current market needs
• Mentorship, mock interviews, and portfolio guidance to prepare for technical and behavioral interviews
• Certification support for IBM, AWS, Microsoft, and other recognized industry credentials
• Career‑focused guidance, including recruiter introductions and placement support
• Flexible and remote‑friendly learning environment
• Opportunities to build and showcase deployable projects in Python, SQL, and ML frameworks