San Fransisco, CA
Job Ref – 14095224
We are seeking a Data Scientist with Computer Vision expertise. The successful candidate will join a product delivery team, following best-practice agile and data science techniques to deliver impactful data products. You will participate in the end-to-end lifecycle of model development, from initial user discovery through data engineering, feature engineering, model training and validation to model deployment as part of a business-facing product. You will actively participate and practice in an open, highly collaborative Agile environment, joining an existing, mature data science practice.
- Applies machine learning and other analytical modeling methods to develop robust and reliable analytical models, including visualizations, within our software development environment.
- Gathers, cleans, transforms, and/or reduces data from dissimilar sources from across our org.
- Collaborates with team members and stakeholders to effectively manage the lifecycle of a model, retraining, replacing or sunsetting models when appropriate.
- Shares and collaborates with other data scientists.
- Delivers best-in-class software as part of a software delivery team.
- Bachelor’s Degree in Econometrics, Economics, Engineering, Mathematics, Applied Sciences, Statistics or job-related discipline or equivalent experience
- Senior Level – Job-related experience, 5 years, OR Master’s Degree and job-related experience, 3 years, OR Doctorate
- Expert Level – Job-related experience, 8 years, OR Master’s Degree and job-related experience, 6 years, OR Doctorate and job-related experience, 3 years
Desired Education / Skills:
- Experience with the data science lifecycle, including data engineering, feature engineering, model building and evaluation, model deployment.
- Knowledge of commonly used data science programming languages, packages, and tools, especially Python.
- Understanding of data science/machine learning models and algorithms, not limited to: deep learning (CNN, RNN etc), decision trees (e.g. xgboost, random forest), unsupervised techniques (e.g. clustering, anomaly detection), natural language processing and statistical methods.
- Experience training models in a public cloud environment, using tools such as Jupyter, AWS Sagemaker.
- Ability to synthesize complex information into clear insights and translate those insights into decisions and actions.
- Ability to clearly communicate complex technical details and insights to colleagues and stakeholders.
- Knowledge of the mathematical and statistical fields that underpin data science
- Knowledge of systems thinking and decomposition of complex problems.
- Humble – is open to being coached, has high EQ and is self-aware
- Hungry – desires to get things done while honoring people, and seeks better ways to do the job
- Collaborative – has strong interpersonal skills; cares about and works well with teammates
- Experience working on an agile delivery team, using methods such as Scrum, Kanban.
- Experience with experimental design and A/B testing.