Junior Statistician

Job Description

We are seeking a passionate, results-driven Junior Statistician with a strong analytical background and a passion for diving into data to discover insights, drive innovation, and impact our product offerings. The ideal candidate will possess a robust understanding of data analytics, statistics, mathematics, experience in model development, and a collaborative spirit to work with cross-functional teams.

Roles & Responsibilities

Key Responsibilities:

• Perform thorough data cleaning and data preprocessing to ensure the accuracy and quality of data.
• Develop and apply statistical models to gain insights, identify trends, and uncover patterns within data sets.
• Engage in the construction and implementation of predictive models to support various business initiatives.
• Work directly and collaborate with the development team to seamlessly integrate analytical models into product offerings.
• Continuously improve model precision and model efficiency through ongoing testing, validation, and refinement.
• Present data-driven insights and predictions to key stakeholders to guide strategic decision-making.
• Stay current with the latest technologies and methodologies in data science and machine learning.

Skills

Preferred Skills:

• Experience with big data technologies (e.g., Hadoop, Spark).
• Knowledge of data visualization tools (e.g. PowerBI).

Qualifications:

• A postgraduate degree (MSc, PhD preferred) in Mathematics, Statistics, or a related field.
• 2-4 years of professional experience in a data analysis or relevant role.
• Solid understanding of machine learning techniques and their real-world advantages/drawbacks.
• Strong experience with data visualization tools and techniques to effectively communicate findings.
• Proficiency in data cleaning, data preprocessing, and data wrangling.
• Experience in developing statistical models and using machine learning algorithms.
• Strong problem-solving skills and the ability to work on complex issues that require in-depth data analysis.
• Excellent communication skills with the ability to articulate results and concepts both verbally and in writing.
• Proven experience in working collaboratively in cross-functional teams.
• A keen eye for detail and a commitment to data integrity.