Role

In this role, you will:

• Identify relevant data sources, collect and clean large structured and unstructured data, and integrate variables into model-building processes. You will also improve model algorithms by conducting error analysis and optimizing performance.
• Communicate key insights from analyses, experiments, and data products to stakeholders, ensuring data-driven decision-making across the organization.

About you

The ideal candidate for this position should:

• Bachelor’s degree in mathematics, statistics, engineering, or analytics related fields. A graduate degree is preferred but not required.
• Solid understanding and practical experience in machine learning techniques, including supervised and unsupervised learning. Proficiency in implementing various algorithms to solve business problems.
• Expertise in statistical models such as regressions, time series analysis, and other predictive modeling techniques to analyze and interpret complex data sets.
• Proficient in programming languages such as Python, PySpark, and SQL, with hands-on experience in writing efficient, reusable code for data analysis and machine learning projects.
• Experience with big data technologies like Hadoop, including the ability to manage and process large datasets in distributed environments.
• Ability to work effectively under the guidance of senior data scientists, contributing to model development and problem-solving while learning and refining new skills.
• Strong communication skills, with the ability to clearly present complex findings and insights to team members, both technical and non-technical, ensuring alignment and understanding of project objectives and outcomes.
• Collaborative mindset, with a willingness to work in a team-oriented environment