Data Scientist

About the Role

Join TWU-Center for Women Entrepreneurs as a Data Scientist in Dunedin, Otago, New Zealand. This role focuses on leveraging data science, machine learning, and AI technologies to enhance lighting products, customer experiences, and business processes. Collaborate closely with senior data scientists, engineers, product managers, and business stakeholders to extract actionable insights from data and implement predictive models in production environments.

Key Responsibilities

• Lead full-cycle data science initiatives to boost product effectiveness, customer satisfaction, and operational workflows.
• Convert business requirements into quantifiable analytical frameworks with clear metrics for measuring success.
• Design, develop, validate, and fine-tune machine learning models and perform statistical analyses under mentorship.
• Work alongside engineering and product teams to integrate models and analytic tools into live systems.
• Employ best-in-class techniques for data preprocessing, feature extraction, model testing, and detailed documentation.
• Effectively communicate technical results and insights to both technical and non-technical audiences.
• Stay abreast of emerging data science and machine learning methodologies that align with company products and objectives.

Candidate Qualifications

• Graduate degree in Data Science, Computer Science, Statistics, or a related discipline.
• Achieved a minimum cumulative GPA of 3.00 across all degrees.
• At least four years of practical experience in data science, analytics, or machine learning roles.
• Strong programming skills in Python or R, with competent knowledge of SQL.
• Understanding of machine learning techniques such as regression, classification, clustering, and time series analysis.
• Experience utilizing machine learning frameworks like scikit-learn, TensorFlow, or PyTorch.

Preferred Skills and Experience

• Hands-on experience deploying machine learning models into production systems.
• Knowledge of cloud platforms such as AWS, Azure, or similar.
• Familiarity with Internet of Things (IoT) or sensor data analytics.
• Exposure to Agile software development methodologies.