Top Hybrid Data Science Jobs in Washington DC
Manager, Data Science role in Consumer Identity Machine Learning at a Fortune 200 company, leading data-driven decision-making using latest machine learning technologies across billions of customer records. Responsibilities include building ML models, partnering with business teams, and writing software to analyze customer data. Ideal candidate is innovative, creative, technical, and statistically-minded.
Lead the AI Foundations LLM Customization team at Capital One to deliver AI powered products that change customer interactions with their money. Utilize technologies like Pytorch, Hugging Face, AWS Ultraclusters, LangChain, and VectorDBs to extract insights from large volumes of data and focus on Natural Language Processing (NLP) for business-specific applications. Collaborate with cross-functional teams to operationalize NLP models in scalable production systems.
Responsible for leveraging data science background to drive compliance monitoring data analytics initiatives, confirming compliance with ethical standards and regulatory requirements through the use of advanced data analytics techniques.
Hiring Data Scientists to bring predictive modeling to the clinical development ecosystem. Responsibilities include building model pipelines, scaling algorithms, enhancing ML Engineering platforms, and implementing ML Ops. Must be familiar with Python and machine learning techniques.
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Seeking a Data Scientist with expertise in data analysis, machine learning, and algorithm development. Responsible for test and evaluation of AI and machine learning models, transitioning algorithms to software applications, and presenting solutions to complex data problems.
Seeking a seasoned data operations professional with 3+ years of experience in analytics, data quality, or data ops role. Responsibilities include owning data pipelines, ensuring data quality, leading integration of new vendors, and collaborating with Data Engineering & Business Intelligence teams. Must have expertise in SQL, schema design, data modeling, and technical tools like Snowflake, Databricks, Redshift, Airflow, and Datadog. Fluency in Python or C# required.
The Data Scientist will be responsible for managing and analyzing in-house and customer data, developing predictive systems, creating algorithms, improving data quality, and implementing statistical analyses. They will work with engineering teams, customers, and research on deploying data analysis systems and applying data science to mission-specific content. Responsibilities include creating algorithms, developing metrics, providing thought leadership, and identifying AI methods for the organization. Qualifications include programming skills, creativity, understanding of distributed computing, and experience with database frameworks and Big Data analytics.
Top hybrid Companies in Washington DC Hiring Data + Analytics Roles
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