Seattle Tech Jobs and Startup Jobs

8

Director, Healthcare Analytics

Accolade
Seattle
3 days ago
+39
The Director of Healthcare Analytics, reporting to the Chief Medical Officer, is responsible for oversight of healthcare analytics for population health management to support Accolade’s Clinical Strategy. This key role will work closely with internal and external partners to ensure the successful delivery of Accolade’s customer commitments. The Director of Healthcare Analytics will be expected have a high level of understanding of health plans and health systems with the ability to analyze large healthcare data sets to identify opportunities to improve clinical operational performance, as well as health care utilization, cost and outcomes. 

Senior Manager, Data Science & Marketplace Ana…

Rover
Seattle
3 days ago
+29
1. Multivariate modeling: the creation of models that lead to better search outcomes, providing better matches between pet sitters and owners. Here, success is measured in terms of impact on marketplace efficiency. 2. Machine learning: the ongoing development of the machine learning infrastructure that enables continuous learning from our data, where success is measured both in terms of marketplace efficiency gains as well as the rate at which different aspects of the user experience are incorporated into our ML systems. 3. Scaling user testing: the parallelization and democratization of end-user testing across all areas of the product and user experience, where success is measured in terms of testing velocity across the organization.

Data Science Manager

Sr. Manager, Big Data Engineer

DreamBox Learning
Bellevue
3 days ago
+22
Manages an organization of BigData engineers. Oversees the hiring and ongoing professional development of the BigData team members. Works on critical, highly complex BigData problems. Works with the team and the rest of the business to plan, share and refine the DreamBox BigData strategy and roadmap. Works efficiently in a collaborative team environment, interacting with technical and nontechnical staff. Seeks to continually improve the BigData software, practices, culture, and results of the team. Establishes and evolves development processes to improve the productivity and efficiency of BigData engineers. Operates at all levels (leadership, management, and individual contribution), inspiring confidence and enthusiasm; happily jumping in and rolling up their sleeves when needed. Partners with leaders across various departments to drive improvements and efficiency in our SDLC process. Helps design and architect BigData solutions and actively participates in architecture discussions with other engineers. Coaches and provides mentorship to the BigData engineers and leaders in the team. Embraces DevOps and agile approaches. Is an active member of an architecture group focused on the big picture of how our software is built, deployed, and operated. Advocates for technology work (such as technical debt) with product managers so that the right mix of core infrastructure and external features get built according to the needs of the business. Leads and manages BigData and BI projects.

Director, Data Science

Getty Images
Seattle
5 days ago
As the head of a quickly growing team, you're an exceptional leader in data science who identifies critical investment areas and influences senior leadership of these strategic directions. You understand the balance between R&D and hands-on product work - you know how to achieve business objectives while developing internal capabilities within the organization. Highly collaborative, you’ve scaled a data science team to meaningful enterprise impact before while boosting the data driven culture of the organization. You want to be empowered to help our customer move the world with images leveraging data 

iQ Research and Development Leader

Qualtrics
Seattle
5 days ago
+27
As the leader of this team you will hire, develop, mentor, and coach both Research Scientists and ML Engineers to ideate and implement new platform features leveraging state-of-the-art techniques in natural language understanding, image classification, statistical modeling, and other forms of ML and AI technology. You will balance important long term R&D investments with short term product deliverables, and partner with PM and company leadership to ensure alignment against strategic and tactical goals.

Research Manager

Manager, Data Science

Convoy
Seattle
1 week ago
+26
Experimental Design. Reduced Form Causal Inference. Auction Design and Optimization. Forecasting/Time Series. Recommendation Systems. Marketplace Dynamics. Prediction/Classification. Operations Research.

Engineering Manager - Data Infrastructure

UX User Researcher

Zipwhip
Seattle
1 week ago
+29
Starting from scratch, this position will create and implement the framework and roadmaps for all product-related research, strategic ad-hoc research initiatives, and UX/UI research. Devise and curate a mixed-methods approach to gathering both generative and evaluative feedback on UX/UI designs and product concepts. Methods may include: in-lab and field studies, online surveys, usability tests, card sorting, moderated and unmoderated remote testing, participatory design, experience mapping, heuristic evaluations, in-depth user interviews, as well as stakeholder interviews. You will supervise a user research manager, and be hands-on and accountable for directly conducting research projects yourself, designing research instruments (surveys, discussion guides) and sampling techniques to gather data with the highest standards. Work collaboratively with our data scientist, business intelligence, and the marketing analytics teams to ensure high quality and maximized impact to effectively communicate research insights and recommendations across Zipwhip. You'll seek out open questions and develop fuzzy unknowns into formal research plans that will empower your team to gain meaningful insights into their customers.

Data Science Engineering Manager

Outreach
Seattle
1 week ago
+16
The Role Data is at the core of Outreach's strategy. It drives our customers and ourselves to the highest levels of success. We use it for everything from customer health scores and revenue dashboards, to operational metrics of our AWS infrastructure, to helping increase product engagement, to predictive analytics and causal inference via experimentation. As our customer base continues to grow, we are looking towards new ways of leveraging our

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