Systems Architect - Data Science & Advanced Analytics to provide strategic and technical leadership in designing, implementing, and modernizing enterprise data and advanced analytics solutions. This role serves as the lead architect for data science initiatives, responsible for developing scalable analytics environments, machine learning solutions, and enterprise data architectures with a strong emphasis on
Databricks,
Apache Spark, and modern cloud-based data platforms.
The ideal candidate will work closely with data scientists, data engineers, business stakeholders, and technical leadership to develop innovative analytics solutions that transform complex data into actionable insights. This individual will provide technical vision, establish best practices, and lead the adoption of advanced analytics and machine learning capabilities across the organization.
Key ResponsibilitiesData Science Leadership- Serve as the Lead Architect for enterprise Data Science and Advanced Analytics initiatives.
- Develop and drive the organization's vision and strategy for Big Data, Artificial Intelligence, and Machine Learning solutions.
- Lead the design and implementation of scalable data science environments that support experimentation, model development, validation, and deployment.
- Provide technical leadership and mentorship to Data Scientists, Machine Learning Engineers, and Analytics teams.
- Identify emerging technologies and analytical methodologies that improve organizational capabilities and mission outcomes.
Advanced Analytics & Machine Learning- Architect end-to-end machine learning and advanced analytics solutions using modern data platforms and distributed computing frameworks.
- Design scalable workflows for data preparation, feature engineering, model training, evaluation, and production deployment.
- Collaborate with cross-functional teams to translate business and mission objectives into advanced analytical solutions.
- Guide the development of predictive models, statistical analyses, optimization models, and AI-driven decision support tools.
- Establish best practices for model governance, reproducibility, documentation, and performance monitoring.
Data Architecture & Big Data Solutions- Design enterprise data architectures that enable large-scale analytics and machine learning workloads.
- Lead the development of data pipelines and analytical frameworks utilizing Databricks Lakehouse architecture, Delta Lake, and Apache Spark.
- Ensure data solutions are scalable, reliable, high-performing, and aligned with enterprise architecture standards.
- Architect integrated data ecosystems that support structured, semi-structured, and unstructured data sources.
- Lead modernization initiatives that enhance data accessibility, analytical capabilities, and operational efficiency.
Strategic Collaboration- Partner with executive leadership and business stakeholders to define data and analytics roadmaps.
- Translate complex technical concepts into business-focused recommendations and strategic initiatives.
- Lead architecture reviews and provide expert guidance on enterprise analytics solutions.
- Foster collaboration between Data Science, Data Engineering, and business teams to deliver high-impact analytical products.
Required QualificationsExperience- Bachelor's degree in Computer Science, Data Science, Statistics, Engineering, Mathematics, or a related technical discipline (Master's preferred).
- 10+ years of progressive experience designing and implementing advanced analytics, machine learning, or Big Data solutions.
- Demonstrated experience serving as a technical lead or subject matter expert for enterprise data science initiatives.
- Experience leading technical teams and architecting large-scale analytics platforms.
- Experience architecting enterprise-scale data science and advanced analytics platforms.
- Experience developing AI/ML solutions supporting mission-critical or large-scale business operations.
- Knowledge of modern data governance and responsible AI principles.
- Experience with experimentation frameworks, model operationalization, and analytical product development.
- Familiarity with Agile product development and collaborative data science workflows.
Required Technical SkillsData Science & Machine Learning- Machine Learning model development and lifecycle management
- Statistical analysis and predictive modeling
- Artificial Intelligence and Advanced Analytics methodologies
- Feature engineering and model evaluation techniques
- Data exploration and analytical solution design
Big Data & Data Engineering- Databricks Lakehouse Platform
- Apache Spark
- Delta Lake
- Distributed data processing frameworks
- ETL/ELT and modern data pipeline architectures
- Data modeling and enterprise data architecture
Analytics & Visualization- Advanced analytics solution design
- Business Intelligence and data visualization concepts
- Dashboard and reporting architecture
- Data storytelling and insight generation
Leadership- Technical strategy development
- Enterprise architecture governance
- Cross-functional team leadership
- Stakeholder engagement and executive communication
- Mentoring and coaching technical teams
Certifications:Candidates should possess one or more of the following certifications:
Databricks- Databricks Certified Professional Data Scientist
- Databricks Certified Professional Data Engineer
- Databricks Certified Machine Learning Associate
- Databricks Certified Developer for Apache Spark
Big Data & Analytics- Apache Spark or Big Data certifications
- Tableau Certified Professional (Desktop or Server)
- Other industry-recognized data science, analytics, or visualization certifications
