Data Scientist 31O25

A Data Scientist is a vital asset to any organization looking to make data-driven decisions. In this role, you will be responsible for extracting actionable insights from large volumes of structured and unstructured data. Your work will involve the use of advanced analytics, machine learning models, and statistical methods to help solve complex business challenges. As a critical thinker and problem solver, you will guide data-driven strategies, tackle intricate data problems, and help drive innovation within the organization. Your expertise will enable you to translate data findings into meaningful narratives that can be communicated effectively to non-technical stakeholders.

Responsibilities

• Analyze large datasets to derive actionable insights and resolve complex business issues.
• Develop, maintain, and optimize data pipelines for data processing and analysis.
• Create predictive models using machine learning techniques to forecast business needs.
• Collaborate with cross-functional teams to understand business objectives and data requirements.
• Visualize data-driven insights via dashboards, reports, and presentations for stakeholders.
• Ensure data integrity and rigor by cleaning, processing, and maintaining quality data sources.
• Translate technical data analyses into clear, actionable recommendations for decision-making.
• Stay updated on the latest data science trends, algorithms, and tools to drive innovation.
• Perform continuous evaluation and improvement of data processes and infrastructure.
• Guide and mentor junior data scientists and analysts within the team.
• Ensure compliance with data privacy regulations and corporate security requirements.
• Facilitate data literacy and advocate for data-informed practices across the organization.

Requirements

• Bachelor's or Master's degree in Data Science, Computer Science, or a related field.
• Proven experience in data analysis, statistical analysis, and machine learning models.
• Strong proficiency in programming languages like Python, R, or SQL.
• Excellent understanding of data wrangling, data visualization, and data mining techniques.
• Ability to communicate complex data insights to non-technical stakeholders effectively.
• Experience with data processing libraries and frameworks such as Pandas, TensorFlow, etc.
• Strong problem-solving skills and the ability to work independently and collaboratively.