Senior Data Scientist

We are looking for talented people to join our Innovative team members. We realize that technically skill talent is always a good addition to our organization. So if you have the required experience and the passion to work with some of the biggest companies in the SF Bay Area, join in!

Responsibilities

We are seeking a Senior Data Scientist for the Data & Analytics Team. The successful candidate will join a product delivery team, following best-practice agile and data science techniques to deliver impactful data products for one of our partners. 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.

• Machine learning and other analytical modeling methods to develop robust and reliable analytical models, including results visualization.
• Gathers, cleans, transforms, and/or reduces data from dissimilar sources from across Client.
• 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.

Education/Experience

• Bachelor's Degree in Econometrics, Economics, Engineering, Mathematics, Applied Sciences, Statistics or job-related discipline or equivalent experience
• Job-related experience, 5 years, OR Master's Degree and job-related experience, 3 years, OR Doctorate
• 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.

Ready to architect a data platform built to last?

\"Zbis is here... Wow!!! It's better than what we expected. This is transformational to our company and how we drive our business forward. It's customer-centric, fact-driven, and captures margins and market-share across all dimensions. Zbis is truly a game changer!\"
- Frederick Howard