Top Remote Senior Level Data & Analytics Jobs
As a Senior Machine Learning Engineer, you will develop robust, scalable ML systems using Python and TensorFlow. You will work collaboratively with Data Scientists to turn prototype algorithms into customer-facing solutions and provide technical leadership to junior team members. Your role also involves building data pipelines, collaborating with Product Managers, and making intelligent technical decisions to enhance personalization capabilities.
The Senior Data Scientist will leverage advanced statistical analysis and machine learning to shape product development and identify opportunities for improvement. They will work with cross-functional teams to deliver analytics solutions and drive the adoption of data products.
As a Principal Data Scientist, you will drive the experimentation practices and analyses, collaborating with business, engineering, and analytics teams, to enable trustworthy decisions at scale. Additionally, you will lead the organization to develop and adopt novel ways to increase the speed of the experimentation lifecycle.
Lead the development and implementation of analytical capabilities and applications, creation of machine learning models and pipelines, development of personalization services, technology proof of concept projects, standardization of machine learning algorithm framework, collaboration with Data Scientists and Analysts, addressing complex technical challenges, analysis of data for insights, and mentoring junior engineers.
Lead Machine Learning Engineer at GoodRx responsible for developing and implementing analytical capabilities, machine learning models, and personalization services. Must have 7+ years of experience in building machine learning systems at scale and expertise in deep learning frameworks such as TensorFlow and PyTorch.
Lead Machine Learning Engineer responsible for developing and implementing analytical capabilities, building machine learning models and pipelines, overseeing technology projects, standardizing machine learning framework, analyzing data for insights, and mentoring junior engineers.
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Seeking a highly motivated Senior Staff Machine Learning Engineer to join Taskrabbit's team and contribute to shaping the future of ML/AI. Responsibilities include designing, developing, and deploying advanced ML models, collaborating cross-functionally on ML projects, and working on modern search platforms using NLP and graph analysis.
As a Senior Data Analyst at Square Banking, you will partner with cross-functional stakeholders to gain insights into customers, drive data-informed decisions, and deliver a remarkable cash flow home experience. Responsibilities include identifying key analytics questions, influencing product roadmap, optimizing funnels, and communicating with high-level partners.
Develop quantitative/machine learning models to forecast product losses, analyze complex datasets, investigate external credit data, automate models and dashboards, and collaborate with various teams to ensure effective communication of loss expectations and trends.
Lead Quality Analyst overseeing QA Analyst group and release management of mobile products. Ensure no errors in mobile software through rigorous testing and adherence to QA procedures. Responsible for test design, execution, maintenance, and closure.
Design and develop data models in Snowflake with DBT, write advanced SQL queries for ELT and data warehousing, collaborate with business partners, promote self-service reporting, and ensure data governance and privacy standards.
Join Iodine Software as a Senior Site Reliability Engineer specializing in managing and growing data platforms. Collaborate with teams on infrastructure projects and provide database performance consultations. Engineer solutions for expanding infrastructure.
Design, develop, and program methods, processes, and systems to analyze big data sources and generate actionable insights. Collaborate with product and service teams to identify questions and issues for data analysis and experiments. Develop software programs, algorithms, and automated processes to cleanse and evaluate large datasets. Communicate insights and findings to stakeholders.
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