Data Scientist

Overview
BukuWarung is SEA’s fastest growing startup and we are building the digital infrastructure for 60 million MSMEs in Indonesia, enabling them to efficiently manage and grow their business, starting with digital bookkeeping, online storefront & payments. BukuWarung’s vision is to empower 60 million MSMEs in Indonesia to become financially aware and enable them to manage and grow their business using technology.
BukuWarung is backed by top tier VCs globally: Peter Thiel’s Valar Ventures, Goodwater Capital, Y-Combinator, AC Ventures, Quona Capital, East Ventures, Golden Gate Ventures, Rocketship.vc, Tanglin Venture Partners and strategic angel investors from Stripe, PayPal, Plaid, Grab, Gojek, Facebook, AirBnB, Fast, Mastercard etc.
About the Team:Data science uses statistical methods, machine learning algorithms and other tools to analyze data and create predictive models; some also build data products, recommendation engines, computer vision models, natural language processing models and other technologies for various use cases that are of high value to our merchants, and high volume in data. We partner with business and product owners across the company, sync and align our insights planning with the Analytics team within the Data function, and work with the Data Product and Engineering teams to enable deployment.
About the Role:The Data Scientist at BukuWarung works on computer vision, natural language processing, and predictive modelling use cases that solve for better predictability, classification, and granularity. Sometimes these approaches are also applicable to information extraction or pattern recognition projects.

What will you do?

• Work with stakeholders throughout the organisation to identify opportunities for leveraging company data to drive business solutions.
• Build various models relevant to the lending business from the ground up - data scorecards, income estimation models, credit models, fraud models etc.
• Extract data from multiple sources. Mine and analyse data from company databases to drive optimisation and improvement of product.
• Work as the data strategist, identifying and integrating new datasets that can be leveraged through our product capabilities and work closely with the engineering team to strategize and execute the development of data products.
• Run data exploration to understand relationships and patterns within the data, develop data visualisation to represent and be able to demonstrate the relationships identified from data exploration.
• Data mining using state-of-the-art methods. Selecting features, building and optimizing classifiers using machine learning techniques.
• Refine and deepen understanding of the algorithmic and inferential aspects of statistical analysis. Evaluate new algorithms from latest research and develop intuition about the problems for which they are likely to improve the state of the practice.
• Present our models to lending partners and get their buy-in 
• Build training pipelines for the production environment. Develop and execute on a plan for continuous iteration and refinement of a new model.

Who are we looking for?

• You have a degree in in Statistics, Computer Science, Mathematics, or another quantitative field
• You have 1 - 3 years of experience as a data scientist manipulating data sets and building statistical models.
• You have a data-oriented personality: strong problem-solving skills with an emphasis on product development.
• You have great communication skills. Excellent written and verbal communication skills for coordinating across teams.
• You have good applied statistics skills such as distributions, statistical testing, and regression.
• Good scripting and programming skills. Experience using statistical computer languages, Python, R, SQL to manipulate data and draw insights from large data sets.
• Excellent understanding of machine learning techniques and algorithms, such as gradient boosting, regressions, k-NN, Naive Bayes, SVM, Decision Forests, and their real-world advantages or drawbacks. Knowledge of deep learning techniques is a plus.
• Experience with common data science toolkits such as R, NumPy, MatLab, Pandas, Scikit-learn, TensorFlow, Keras etc.
• Experience with data visualisation tools such asD3.js, GGplot.
• Proficiency in using query languages such as SQL

If this sounds like you, please apply!