Senior Data Science Architect

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The Senior Data Science Architect designs, develops, and programs methods, processes, and systems to consolidate and analyze unstructured, diverse “big data” sources to generate actionable insights and solutions for client services, business requirements, and product enhancement. Interacts with product and service teams to identify questions and issues for data analysis and experiments. Develops and recommends software programs, algorithms, and automated processes to cleanse, integrate and evaluate large datasets from multiple disparate sources. Identifies meaningful insights from large data and metadata sources; interprets and communicates insights and findings from analysis and experiments to product, service, and business managers.
The primary responsibility
1. Data Strategy: Develop and implement an enterprise-wide data strategy aligned with business objectives.
2. Data Modeling: Create and maintain data models to define data structures, relationships, and standards.
3. Data Governance: Establish and enforce data governance practices, including data quality, privacy, and compliance.
4. Data Integration: Design and optimize data integration processes to ensure data flows seamlessly across systems.
5. Data Security: Implement security measures to safeguard sensitive data and ensure compliance with corporate data security standards.
6. Database Management: Manage and optimize databases, including performance tuning, backup, and recovery.
7. Data Architecture: Design and maintain the organization's data architecture, considering scalability and future needs.
8. Collaboration: Collaborate with cross-functional teams, including data engineers, analysts, and business stakeholders, to define data requirements and solutions.
9. Documentation: Maintain comprehensive documentation and catalog of data architecture, standards, and processes.
10. Technology Evaluation: Stay updated on emerging technologies and recommend tools and platforms that align with the company's data strategy.

Working at NTT

ESSENTIAL DUTIES & RESPONSIBILITIES

• Collaborate with business stakeholders to identify opportunities for leveraging data to drive business solutions
• Research, design, implement and deploy scalable data analytics vision to challenge complex business issues
• Extending company’s data with third party sources of information when needed
• Enhancing data collection procedures to include information that is relevant for building analytic systems
• Processing, cleansing, and verifying the integrity of data used for analysis, and building algorithms necessary to find meaningful answers
• Perform analysis using programming languages or statistical packages
• Mine and analyze data to drive optimization and improvement of business strategy
• Architect scalable and highly available applications leveraging the latest tools and technologies
• Creatively visualize and effectively communicate results of data analysis, insights, and ideas in a variety of formats to key decision-makers within the business
• Take ideas to successful launch by leading and mentoring diverse, geo-distributed teams through innovation, bootstrapping, pilot, production, scaling, and maintenance phases with multiple stakeholders to the highest levels of quality and performance
• Develop SQL Queries for reports and dashboards
• Analyze relational and transactional databases to provide data analysis, and present results in a clear manner
• Create documentation around processes and procedures and manage code reviews
• Apply industry standards best practices to development activities
• Work on data set to ensure solutions are successfully executed, within agreed upon time frames

KNOWLEDGE, SKILLS & ABILITIES

• Subject matter expertise in data modeling
• Theoretical understanding of statistical methods and modern techniques
• Ability to thrive in a dynamic, fast-paced environment
• Excellent quantitative and qualitative analysis skills
• Strong desire to acquire more knowledge in order to keep up to speed with the ever-evolving field of data science
• Strong curiosity to sift through data to find answers and more insights Solid understanding of the information technology industry within a matrixed organization and the typical business problems such organizations face
• Ability to clearly and fluently translate technical findings to non-technical team business stakeholders to enable informed decision-making
• Ability to create a storyline around the data to make it easy to interpret and understand
• Theoretical understanding of statistical methods and modern techniques
• Self-driven and able to work independently, yet acts as a team player