Senior Machine Learning Scientist
Zeitworks is a Seattle based, venture-backed startup on a mission to streamline business process improvement and maximize human potential at work. We are looking for a product focused, results-oriented Senior Data Scientist who is excited to play a major role in our product and engineering evolution to build out a secure and scalable automated data pipeline and ML/AI capabilities.
Organizations across the globe want to deliver greater value to their customers by improving their business processes. But they lack visibility and insight both into how these processes are actually performed and where to invest to drive the greatest impact. Traditionally delivering these improvements required expensive consultants, obtrusive over-the-shoulder observations, and countless meetings; taking months or years to deliver value.
Looking beyond automation, Zeitworks uses proprietary ML and AI to automatically discover, analyze and improve all an organization’s business processes, with zero disruption, to provide real-time business insights to business leaders. Our friction-free SaaS delivery allows us to democratize process improvement providing on-going value to business leaders in days rather than months.
ROLE AND RESPONSIBILITIES
The Senior Machine Learning Scientist will have a background in machine learning environments, have experience working with large data sets, and have a track record of building and deploying data-driven innovative AI solutions. Reporting to the CTO, you will be driving the discovery and usage of new models, participate in the technical DS/ML direction of the product, and work on end-to-end data systems within the data science process. You will work with the other members of the development team and data science team to ensure both the accuracy and validity of the data, as well as the customer value of the resulting analytics and recommendations.
Additional Responsibilities & Requirements:
- Play a senior and leadership role within the data scientist org helping the team, product, data, and performance continue to scale
- Work hand in hand with the CTO to drive and implement ML approaches
- Evangelize new solutions, approaches, and technologies, and stay at the cutting edge of ML Engineering
- Productionalize and deploy machine learning models
- Create ML frameworks and backend services for use across the organization, with a focus on scalability, performance and extensibility
- Strong experience with data mining techniques: XGBoost, text mining, GLM/Regression.
- Natural Language Processing (NLP) and Image Processing : CNN with neural network model experience
- Experience with Cloud services, Amazon Web Services (AWS), or similar (e.g. EC2 instances, AWS Comprehend API, AWS S3, AWS Data Lake)
- Experience with feature selection, model building, and optimization using supervised and unsupervised machine learning techniques to support analytic objectives
- Participate in our engineering life-cycle, including designing high-quality ML infrastructure and pipelines, writing production code and participating in code reviews
- Possession of excellent oral and written communication skills
- Maintain a strong focus on business outcomes
- Experience working in early stage startups
Everyone on the Zeitworks' team is expected to demonstrate the following characteristics:
- Scrappy - experience doing a lot with limited resources
- A strong sense of customer empathy
- Strong collaborator, listens without judgement, respectful of others
- Self-disciplined and process minded
- Adaptable, comfortable taking risks
- Picking up balls, holding self-accountable, holding others accountable
- Pragmatic: experience with stage-appropriate architecture and development - crawl, walk, run
- Open, transparent, flexible
Zeitworks values inclusion and believes diversity at all levels as this will enable us to best accomplish our mission. We aspire to be among the tech industry’s most inclusive work environments and are a proud equal opportunity employer. We are committed to providing equal opportunities without regards to race, color, religion, creed, gender, national origin, age, sex, gender expression or identity, sexual orientation, political affiliation, pregnancy or related medical conditions, disability status, marital status, or reservist/veteran status.