Top Software Data Science Jobs

Remote data science role to analyze large datasets, build/train/deploy machine learning models, design data pipelines, create visualizations, and collaborate with stakeholders to drive data-driven solutions.

Perform large-scale data analysis and modeling using Hadoop ecosystems and general-purpose languages (Java, Python, R). Apply statistical techniques and machine learning on big datasets, develop creative solutions, visualize patterns, and work independently within a research-oriented team. Strong communication and rapid conceptual learning are expected.

Integrate and analyze large, disparate datasets using statistical methods and machine learning to generate actionable business insights. Build and validate predictive models, analyze unstructured data, and present findings to stakeholders. Manage project budgets and timelines, and apply industry knowledge to deliver on-time, on-budget analytics solutions.

As a Data Scientist at Retool, you will analyze customer behavior and business performance, build analytical models, and provide insights to guide strategy across teams.

The Data Scientist will apply machine learning and statistical analysis to support mission analysis, develop analytical tools, and visualize complex datasets for insights.

Seeking a Senior Data Scientist to design, code, and improve models and algorithms, evaluate decision systems, and partner with teams to translate data into impactful behaviors.

Seeking a skilled Data Scientist/Machine Learning Engineer to develop machine learning models, design AI systems, and collaborate in data analytics. Responsibilities include productionizing models, data engineering, and cross-functional collaboration.

Use large company datasets to build, validate, and deploy predictive models and algorithms to optimize product, marketing, and business outcomes. Partner with stakeholders to identify opportunities, implement models, monitor performance, and ensure data accuracy. Analyze third-party analytics and distributed data sources, create data architectures, and present insights to cross-functional teams.

Perform statistical and computational analysis on large, messy datasets to produce defensible conclusions. Build analytic models, perform statistical inference and prediction, translate mission needs into technical requirements, and communicate results to non-technical stakeholders. Maintain awareness of collection/processing limitations and recommend technical solutions.

Analyze large-scale educational data to inform product design and efficacy. Develop, evaluate, and maintain statistical and AI models, collaborate with cross-functional teams, communicate findings to stakeholders, and leverage AI tools for analysis and feature engineering while following software development practices.