Data Scientist, Data Architect

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🏄 California – Remote

🏄 California – Remote

💵 $215k - $265k / year

⏰ Full Time

🟠 Senior

🔴 Lead

🚰 Data Engineer

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DDN

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

Founded 1998

🤖 Artificial Intelligence

💰 $10M Funding Round on 2011-06

Artificial Intelligence • Data Center and Cloud Computing • High Performance Computing

DDN is a global leader in AI data intelligence solutions, providing high-performance computing and sophisticated data management technologies. With a focus on accelerating AI deployments and advanced data analytics, DDN's products, including the Data Intelligence Platform and advanced storage systems, serve diverse sectors such as healthcare, financial services, and government. DDN is committed to transforming enterprise data infrastructure to leverage the full potential of AI and drive operational efficiency.

📋 Description

• Develop machine learning and AI solutions to solve business and operational challenges • Design, build, validate, and deploy models for forecasting, anomaly detection, customer analytics, capacity planning, and product intelligence • Apply statistical analysis and experimentation techniques to generate actionable insights • Develop dashboards, visualizations, and executive-level reporting to communicate findings and recommendations • Monitor model performance and support continuous improvement initiatives • Partner with business stakeholders to define key metrics, KPIs, and success measures across products and operations • Design scalable enterprise data architectures supporting structured, semi-structured, and unstructured data workloads • Define data models, metadata standards, governance frameworks, and architectural best practices • Architect modern data platforms leveraging cloud, hybrid-cloud, lakehouse, and distributed data technologies • Establish data integration strategies across CRM, ERP, product usage, support, operational, and business systems • Build scalable ETL/ELT pipelines and data services that support analytics and AI workloads • Drive adoption of data quality, lineage, security, privacy, and compliance standards • Partner with product, engineering, and business leaders to identify high-value AI and analytics opportunities • Build reusable data products, semantic layers, and self-service analytics capabilities • Support AI initiatives involving LLMs, RAG architectures, vector databases, and enterprise knowledge systems • Collaborate with software engineering teams to operationalize analytics and AI capabilities in production environments • Contribute to the development of intelligent platform features that improve customer experience and operational efficiency • Serve as a trusted advisor on data strategy, architecture, and analytics best practices • Lead technical design reviews and architecture discussions • Mentor data scientists, data engineers, and analysts • Communicate technical concepts and recommendations to both technical and non-technical audiences.

🎯 Requirements

• Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Applied Mathematics, Engineering, or a related field • 8+ years of experience in data science, data architecture, analytics engineering, or related disciplines • Strong proficiency in Python and SQL • Experience building and deploying machine learning models in production environments • Deep understanding of data modeling, ETL/ELT pipelines, and modern data platform architectures • Experience with cloud platforms such as AWS, Azure, or Google Cloud • Hands-on experience with distributed data processing technologies such as Spark, Databricks, Snowflake, BigQuery, or equivalent platforms • Strong knowledge of statistics, experimentation, forecasting, and predictive analytics • Excellent communication and stakeholder management skills • Experience working with AI platforms, cloud infrastructure, SaaS products, or large-scale distributed systems • Experience with MLOps, DataOps, CI/CD, and model lifecycle management • Familiarity with vector databases, retrieval systems, LLMs, and generative AI architectures • Experience with Kubernetes, containerized environments, and cloud-native platforms • Knowledge of data governance, security, privacy, and regulatory frameworks • Experience leading enterprise-scale data transformation initiatives.

🏖️ Benefits

• Competitive salary • Health insurance • Retirement plans • Professional development opportunities