Data Science Manager

About the Company

• 💰  Early-stage, ed-tech, funded, growing, growing fast.
• 🎯  Mission Driven: Make Indonesia competitive on a global scale.
• 🥅  Build the best educational content and technology to advance STEM education 
• 🥇  Students-First approach

About the People

• ❤️  Love what we do
• 🎮  Committed to making learning fun, accessible, and safe 
• 🤝  Teams are better. We value ownership, responsibility, transparency
• 🌏  Global, diverse backgrounds. Been there, done that.

What does it look like one year from now?

• CoLearn has grown so much, and you’ve been an important part of the growth. You solved hard problems that many didn’t know existed.
• You’ve led the data science function and laid out the roadmap, implemented best practices, and grown the team. You’ve executed mission-critical projects. Congratulations!
• You’re exploring what Data Science can do for the students, parents, teachers, educators.
• You’ve been speaking at Data Science conferences about the image recognition system we built from scratch. You casually threw in the semantic search engine on slide 77.
• The engineering and product teams are your friends. The teams take cross-functional collaboration, testing, and modeling for granted. It’s their second nature.
• You have an encyclopedic knowledge of CoLearn’s data structures and metrics, and you’ve often provided key ideas for the product.

About you

• Highly-skilled and experienced Data Scientist and leader
• You are interested in creating next-gen data-powered education tech products. 
• You’ve worked in a Data Science role before where you took a data product to market
• You are comfortable working with unknowns, evaluating the data, and applying scientific techniques to business problems and products
• You’ve built platforms and systems from scratch
• You have a track record of developing and deploying data-science models to production

Let’s talk tech

• End-to-end AI/ML systems in the cloud, including data processing, feature engineering, and tuning of ML models in training and production (MLOps) — with both structured and unstructured data.
• Deep Learning and Computer Vision models, ideally in a production environment
• Hands-on Python/SQL, scikit-learn, Keras, PyTorch, Tensorflow, MXnet, etc. 
• Experience in Scala/Java/Go/C/C++ is a plus plus
• Airflow/Luigi/Oozie and the likes
• Familiarity with cloud deployment strategies (AWS/GCP) to deploy at scale

Track record

• B.S./B.E./M.S./PhD in a quantitative field such as Computer Science, Engineering, Math, Statistics or equivalent years of experience
• 10+ years of experience in data science, algorithmic engineering, and machine learning. Preferably solved problems from scratch to scale
• Experience in hiring, managing highly-performant teams, and mentoring data science, data engineering, and analytics teams 
• Experience developing a data science strategy, building the roadmap, and leading the execution
• Track record of recruiting talent in analytics and data science

You will make us go 😍 if:

• You’ve won algorithm and machine learning competitions such as ACM and Kaggle
• You have research publications and citations in top tier journals 
• You have a portfolio of side projects and can show it to us

Does this sound like a match? Or maybe a bit too much? Don’t agree with something here? Let’s talk.