Data Scientist 30N25

As a Data Scientist at 30N25, you will play a crucial role in unraveling the potential of data to drive decision-making and strategy development across various departments. Your analytical prowess and affinity for data will enable you to transform complex datasets into actionable insights and innovative solutions. Working alongside cross-functional teams, you'll harness the power of cutting-edge statistical algorithms, machine learning techniques, and state-of-the-art data technology to solve challenging business problems. If you have a curious mind, a passion for data, and the ability to translate sophisticated data-driven outcomes into tangible business actions, this is your opportunity to make a significant impact in our dynamic organization.

Responsibilities

• Design and implement advanced predictive models using statistical analysis and machine learning.
• Gather, clean, and preprocess large datasets from multiple sources to ensure data integrity.
• Collaborate with cross-functional teams to identify data-driven solutions and business strategies.
• Develop and maintain scalable data pipelines to support ongoing analytics projects.
• Conduct exploratory data analysis to uncover trends, patterns, and insights.
• Create comprehensive reports and visualizations to effectively communicate analysis results.
• Stay updated with the latest industry trends and advancements in data science and analytics.
• Optimize and fine-tune algorithms to improve model performance and accuracy.
• Provide mentorship and guidance to junior data scientists and analysts.
• Work closely with technology teams to integrate data models into production environments.
• Ensure adherence to data governance and privacy policies throughout the project lifecycle.
• Participate in brainstorming sessions to promote a culture of continuous improvement.

Requirements

• Bachelor's or Master's degree in Data Science, Mathematics, Statistics, or a related field.
• Proven experience in data science roles with a strong analytical skill set.
• Proficiency in programming languages such as Python, R, or SQL for data analysis.
• Solid understanding of machine learning algorithms and statistical modeling techniques.
• Experience with data visualization tools such as Tableau, Power BI, or similar.
• Strong problem-solving skills and ability to work both independently and collaboratively.
• Excellent communication skills to present complex findings to diverse audiences effectively.