Junior Data Scientist

You will join a forward-thinking organization where data is the language of decision-making. We are a team of intellectually curious innovators dedicated to solving complex problems across a multitude of industries. Our culture fosters continuous learning and provides robust mentorship opportunities to help you grow into a world-class data professional..

Your Impact and Responsibilities

- Conduct comprehensive exploratory data analysis to uncover hidden patterns and trends within large, intricate datasets from industries like finance, healthcare, and e-commerce.

- Develop, train, and validate foundational machine learning models—including regression, classification, and clustering—to address critical business challenges and predict future outcomes.

- Execute rigorous data wrangling and preprocessing (cleaning, transforming, and augmenting data) to ensure the highest quality inputs for your analytical and modeling efforts.

- Translate complex analytical findings into compelling narratives and visualizations using tools like Tableau or Matplotlib, making your insights accessible to non-technical stakeholders.

- Collaborate on the end-to-end data science lifecycle, from hypothesis generation and data collection through to model deployment and performance monitoring.

- Assist in designing and interpreting A/B tests and other statistical experiments to validate hypotheses and guide strategic decisions.

- Meticulously document your code, methodologies, and findings to ensure reproducibility and foster knowledge sharing across the team.

- Support the integration of your models and analytical modules into broader AI-driven applications and products.

Core Qualifications and Skills

- A Bachelor’s or Master’s degree in a quantitative field such as Computer Science, Statistics, Mathematics, Data Science, or a related discipline.

- Foundational proficiency in Python for data analysis, particularly with libraries like Pandas, NumPy, and Scikit-learn. Familiarity with R is a significant plus.

- Solid understanding of core machine learning concepts, algorithms, and statistical principles (e.g., probability, hypothesis testing).

- Demonstrable experience writing and optimizing SQL queries to extract and manipulate data from relational databases.

- Experience creating clear and effective data visualizations with tools such as Tableau, Power BI, Matplotlib, or Seaborn.

- Exceptional problem-solving abilities and a structured approach to tackling ambiguous questions with data.

- Strong communication skills, with the ability to articulate technical concepts and the story behind the data to diverse audiences.

- An insatiable curiosity and a commitment to continuous learning to stay current with the latest techniques and technologies in the field.