What are the responsibilities and job description for the AMER: Principal Data Scientist position at Algolia?
Algolia is the industry’s leading search-as-a-service provider, the search experience of the world’s best brands. Today, Algolia powers 1.5 trillion searches a year, for 10K customers in over 200 countries and 70 languages. As a fast-growing company, we are looking for passionate talents to join the adventure.
You’ll be joining the Growth Team. The Growth team aims to help Algolia grow by providing the best possible user experience, which facilitates our users to realise the value of Algolia’s products.
You will be responsible for building ML solutions that tie into our Product Led Growth effort across the Algolia Product Portfolio. This is a unique opportunity to influence and contribute to all stages of product development and harness the power of machine learning for highly visible initiatives. Algolia is a successful and fast-growing company. By joining at this stage of the company you’ll be able to set the foundations of how the company will leverage data in the short and long term future.
You will build models that inform us how to think better about our PLG business. As part of this, you will build out propensity models for different cohorts of customers, define the lifecycle of customers on our platform, build sensing mechanisms that tell us when customers are approaching lifecycle transition points, and in the process help measure our business in ways we’re not currently able to. Your level of excellence and accountability allows you to report to executive leadership.
You may be a fit if you have:
- 8 years of hands-on industry experience building supervised and unsupervised learning models
- A Masters or PhD in Artificial Intelligence, Computer Science, Mathematics or Statistics.
- Strong background in Machine Learning, statistical inference or similar. Building predictive models is your game. You have knowledge about regression, deep neural networks, cross validation, naive bayes, feature extraction, feature engineering, overfitting, etc.
- Strong programming skills. Hands-on machine learning experience with Python and toolkits like PyTorch or TensorFlow.
- Track record of building, shipping and maintaining machine learning models in a highly ambiguous and fast paced environment.
- Track record of defining new data science techniques and best practices that improve the ML model performance.
- Track record of designing and architecting large scale experiments and analysis which impact multiple teams and adjacent focus areas.
- Experience with Deep Learning and associated frameworks is a plus.
- Experience with data processing infrastructure such as Spark, Hadoop, SQL, Amazon Web Services and/or Google Cloud Platform is a plus.
- Experience supporting product or growth teams
- Experience in the SaaS industry
- Experience working with executive leadership, across departments/teams
- Preference for candidates with experience at our current stage and beyond (over 10,000 customers, high growth, lots of change and building internal processes)
