What youll do :

- Design, build, deploy and refine large-scale machine learning models and algorithmic decision-making systems that solve real-world problems for customers.

- Work cross-functionally with commercial stakeholders to understand business problems or opportunities and develop appropriately scoped analytical solutions.

- Collaborate closely with various engineering, infrastructure, and ML platform teams to ensure adoption of best-practices in how we build and deploy scalable ML services.

- Identify new opportunities and insights from the data (where can the models be improved? what is the projected ROI of a proposed modification?).

- Be obsessed with the customer and maintain a customer-centric lens in how we frame, approach, and ultimately solve every problem we work on.

We Are a Match Because You Have :

- Bachelor's or Masters degree in Computer Science, Mathematics, Statistics, or related field.

- 6-9 years of industry experience in developing machine learning algorithms.

- Proficiency in Python or one other high-level programming language.

- Solid hands-on expertise deploying machine learning solutions into production.

- Strong theoretical understanding of statistical models such as regression, clustering and ML algorithms such as decision trees, neural networks, etc.

- Strong written and verbal communication skills, ability to synthesize conclusions for non-experts, and overall bias towards simplicity.

- Intellectual curiosity and enthusiastic about continuous learning.

Nice to have :

- Experience with Python ML ecosystem (numpy, pandas, sklearn, XGBoost, etc.) and/or Apache Spark Ecosystem (Spark SQL, MLlib/Spark ML).

- Familiarity with GCP (or AWS, Azure), ML model development frameworks, ML orchestration tools (Airflow, Kubeflow or MLFlow).

- Experience in information retrieval, query/intent understanding, search ranking, recommender systems etc.

- Experience with deep learning frameworks like PyTorch, Tensorflow, etc.