Data Scientist I

Responsibilities & Accountabilities

• Collect, organize, and pre-process data from various sources.
• Apply statistical concepts, analyze data, and present insights using visualisations.
• Use Python / Spark to build and interpret machine learning models.
• Create well-documented code and conduct thorough testing of AI modules.
• Collaborate with the team, seek guidance, and actively contribute to discussions.
• Align data science efforts with product goals and effectively communicate insights.
• Stay updated with emerging technologies and proactively learn new methodologies.
• Adhere to ethical data handling practices and comply with regulations.
• Understand and consider stakeholder goals and requirements.
• Apply analytical tools to solve problems and ensure a user-centric approach in product development.

Educational and Experience Requirements

Degree: Bachelor's in Data Science, Computer Science, Statistics, Mathematics, or related field.

Practical Experience: Internships, projects, or academic experience in data analysis, modelling, or related roles.

Programming Proficiency: Proficient in Python, demonstrated through projects or practical applications.

Data Manipulation and Analysis: Experience in data manipulation and analysis using appropriate tools.

Collaborative Projects: Collaboration on team projects, showcasing problem- solving and teamwork abilities.

Application of Data Science: Application of data science concepts to real-world problems through academic projects or internships.

Adaptability and Learning: Demonstrated ability to learn and adapt to new technologies and methodologies.

Communication Skills: Effective communication skills demonstrated through presentations or project reports.

Ethical Data Handling: Understanding and adherence to ethical guidelines and responsible data handling practices.