Associate Data Scientist

We are a rapidly growing, innovation-led company dedicated to solving complex challenges through data. Our teams operate at the intersection of diverse industries like technology, finance, and healthcare, delivering solutions that redefine industry standards. By fostering a culture of continuous learning and collaboration, we empower our people to push the boundaries of what's possible with artificial intelligence and machine learning. You'll be joining a collective of brilliant minds focused on creating tangible, measurable value from data. Our commitment to a flexible, remote-first culture means you can contribute from wherever you work best.

What You Will Do

- Perform comprehensive exploratory data analysis (EDA) on large, intricate datasets to uncover hidden trends, crucial patterns, and significant anomalies that will inform business strategy.

- Design, build, and rigorously test statistical and machine learning models—from linear regressions to more complex gradient boosting machines—to address critical business questions and drive predictive insights.

- Execute robust data cleaning, transformation, and feature engineering (data wrangling) to construct high-quality, reliable datasets essential for accurate modeling.

- Develop compelling, interactive data visualizations and executive-level dashboards using tools like Tableau or Matplotlib to communicate complex findings effectively to both technical and non-technical stakeholders.

- Actively collaborate on the end-to-end AI project lifecycle, contributing to everything from initial hypothesis generation and experimental design (including A/B testing) to model validation, deployment monitoring, and thorough documentation.

- Write clean, efficient, and well-documented Python code, leveraging core data science libraries to support all phases of data analysis and model implementation.

- Present your analytical findings and strategic recommendations clearly and persuasively, using data to tell a story and champion data-informed decision-making across the organization.

What You Bring to the Table

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

- Demonstrable proficiency in Python for data analysis, including hands-on experience with libraries like Pandas, NumPy, and Scikit-learn.

- Solid understanding of core statistical concepts and machine learning algorithms (e.g., regression, classification, clustering).

- Experience querying databases using SQL to extract and manipulate data for analytical purposes.

- Familiarity with at least one data visualization tool (e.g., Tableau, Power BI, Matplotlib, Seaborn).

- Exceptional problem-solving abilities and a curious mindset… you love digging into data to find the "why".

- Strong communication skills, with the capacity to explain complex technical concepts to diverse audiences.

- A collaborative spirit and the ability to work effectively within a distributed, remote team environment.

Preferred Qualifications

- Experience with R for statistical computing is a significant advantage.

- Exposure to cloud computing platforms (AWS, Azure, or GCP) and their data services (like S3, Redshift, or BigQuery).

- Familiarity with version control systems, particularly Git and GitHub.

- Previous internship or project experience in data science, business intelligence, or a related analytical field.