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Data Scientist III

Kueski

Kueski

Data Science
Mexico
Posted on Wednesday, July 10, 2024
About Kueski
At Kueski, we're dedicated to improving the financial lives of people in Mexico. Since 2012, we've been the leading buy now, pay later (BNPL) and online consumer credit platform in Latin America, known for our innovative financial services. Our flagship product, Kueski Pay, provides seamless payment solutions for both online and in-store transactions, establishing itself as the preferred option for a quarter of Mexico's top e-commerce merchants. Notably, we were the first to introduce BNPL on Amazon Mexico.
We're a tech company with a culture geared toward innovation, collaboration, and impact, fostering a strong, diverse, and inclusive company culture. In 2023, Kueski was recognized as the top BNPL platform by Fintech Breakthrough and earned the title of one of Mexico's most ethical companies from AMITAI. Additionally, we ranked as one of the Best Companies for Female Talent by EFY.
Purpose
Over half of the Mexican population lacks access to financial products due to traditional banking limitations. Kueski aims to provide financial opportunities through technological innovation.
Our data science team at Kueski is crucial in achieving this mission, developing machine learning technology for real-time risk assessments, resource optimization, and personalized customer offers. Collaboration is key, with data scientists working closely with machine learning engineers, software engineers, risk and business analysts, and product managers.
Data scientists build models, analyze data, and understand business needs using advanced open-source libraries and cloud technology, contributing to reliable production machine learning pipelines.
At Kueski we seek an analytical, quantitatively skilled individual passionate about applying machine learning to product development.

Key Responsibilities:

  • Data scientists help to build, shape, and improve our products using machine learning and data analytics
  • They are able to collaborate with stakeholders from different teams in order to develop reliable machine-learning technology
  • Their maturity and soft skills allow them to build collaborative relationships with stakeholders from different areas. With their experience and technical understanding, they are able to push technical excellence and contribute to the growth of team members
  • You are the owner of production machine learning models. This means you are responsible for tracking performance KPIs, making sure they remain in acceptable pre-defined levels, and taking action if they don’t
  • Have autonomy to collaborate with stakeholders from other areas, developing enhancements to our products
  • Perform data analysis which helps us understand better the performance of our products, their usage, and areas of opportunity
  • Perform data analysis which helps us find population segments where our Machine Learning models underperform
  • Develop new model experiments and feature engineering
  • Participate in different stages of our product development framework, providing input to stakeholders from Product and Engineering and defining requirements for the features to be developed by engineering teams which might impact the work of data scientists
  • Provide mentoring to team members, pushing technical excellence and business expertise
  • Perform code reviews with other team members
  • Understand the work of other team members and provide feedback
  • Perform data analysis which helps us understand better the performance of our products, their usage, and areas of opportunity
  • Perform data analysis which helps us find population segments where our Machine Learning models underperform
  • Develop new model experiments and feature engineering
  • As the owner of a production machine learning model, you must create adequate documentation for your whole machine learning pipeline (feature engineering, feature selection, hyperparameter tuning, algorithm selection, performance KPIs, acceptable levels of performance KPIs, business usage, business KPIs, etc.)
  • Provide support to recruiting processes (evaluation of challenges, etc.)
  • Perform ad-hoc drill-down analyses to understand anomalies or performance degradations seen in production
  • Work closely with MLEs or QA engineers to develop the QA process of your production models

Position Requirements:

  • To have a quantitative background. For example, a degree in fields such as Engineering, Physics, Mathematics, or similar experience and competencies.
  • Strong analytical skills
  • Strong skills to communicate clearly and effectively data science analyses and reports both to technical and non-technical audiences
  • Advanced understanding of the internal working of Machine Learning algorithms, and proven experience using them in academy or industry applications
  • Experience learning and implementing new technologies and methodologies
  • Extensive experience collaborating with stakeholders from different areas, addressing business problems effectively by means of machine learning applications
  • Maturity and well-developed soft skills to influence team members and stakeholders from other teams, and have effective conversations when opinions may differ
  • Consistent experience working autonomously on data science projects with considerable impact on the company, and contributing to the improvement of the team's performance
  • Ability to mentor junior team members, and pair effectively with team members on a project
  • Strong analytical mindset and background
  • Strong skills using analytical tools like pandas, numpy, matplotlib, etc
  • Strong skills using Machine Learning libraries
  • Solid SQL skills
  • Feels comfortable using a Unix-like OS
  • Fluency in English
  • Clear communication to non-technical audiences
  • Nice to have: Experience working with AWS technologies specific to machine learning

You’ll love working at Kueski because:

  • We have a mission-driven culture focused on customer value, teamwork, humility, and integrity
  • Everyone is expected to have role clarity, career growth, and a personal development plan. Feedback and recognition are embedded in our company processes, systems, and practices
  • We ensure competitive salary, medical insurance, and wellbeing through ample and flexible time off as well as mental healthcare benefits
  • Everyone is an owner and eligible for competitive stock options with a company poised for success. We're committed to building an inclusive and diverse team and we know this leads to incredible work
Kueski: Where talent excellence improves Mexican lives.
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