Junior Data Scientist

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About the Role

Junior Data Scientists will contribute to the delivery of enterprise-wide analytics services, with a focus on advanced statistical modeling, machine learning, and AI-driven forecasting.

Responsibilities include building data pipelines, automating analytical workflows, and presenting actionable insights to internal stakeholders, including executive leadership. The successful candidates will demonstrate proficiency in Python, SQL, and data visualization tools, and possess a strong understanding of supervised and unsupervised learning techniques, time series forecasting, and model performance evaluation.

Key Responsibilities

• Develop and implement robust statistical and machine learning models.
• Select and apply appropriate modeling techniques to ensure the accuracy, interpretability, and reliability of analytical outcomes.
• Conduct comprehensive data analysis to generate actionable insights that support strategic objectives, working closely with the Senior Data Scientist to prioritize key variables and analytical approaches.
• Design and maintain automated workflows and data pipelines to streamline repetitive analysis tasks and enable timely delivery of insights.
• Source, clean, and transform large and complex datasets from multiple systems, ensuring data integrity and analytical readiness through rigorous preprocessing techniques.
• Collaborate with stakeholders and interdisciplinary teams to identify data requirements, extract relevant information, and enable a unified view across data sources.
• Assist in preparing and delivering analytical findings to both technical and non-technical audiences
• Respond to stakeholder inquiries by conducting supplementary analyses, addressing methodological concerns, and clarifying recommendations in alignment with strategic priorities.
• Translate complex data outputs into clear, actionable recommendations to guide data-informed decision-making.

Required Qualifications

• A bachelor's degree in Data Science, Computer Science, Statistics, or a related discipline
• Solid grounding in statistical methodologies, machine learning techniques, and modern data visualization practices.
• Proficiency in programming languages such as Python, R, and SQL, along with hands-on experience using analytical libraries and frameworks including Pandas, NumPy, Scikit-learn, or comparable tools
• Familiarity with data visualization platforms such as Power BI, Tableau, or libraries like Matplotlib and Seaborn to effectively communicate data-driven narratives.
• Exceptional attention to detail and strong capabilities in analytical thinking, problem-solving, time management, and organizational execution, with the ability to manage tasks independently.
• Strong interpersonal, teamwork, and communication skills, with demonstrated success in delivering complex analytical findings to both technical and non-technical stakeholders through clear verbal, written, and visual presentations.
• Proven commitment to continuous professional development and staying current with emerging trends in data science, advanced analytics, machine learning, and data visualization technologies.

More

• Proficiency in SQL queries
• Experience using large language models
• Experience with Power BI



About the Company

The organization is a leading research-focused institution committed to innovation and real-world impact. With a diverse and collaborative environment, it drives progress through data-driven solutions and interdisciplinary expertise. The data science team tackles complex problems using advanced analytics and machine learning, delivering tailored, high-impact solutions that support strategic goals across various sectors.