The Senior Architect, Data Science, plays a critical role in designing and implementing the data science architecture that drives our organization's data-driven initiatives. With a deep understanding of data science principles, machine learning, and big data technologies, this position requires extensive experience in architectural design and leadership. The Senior Architect collaborates with cross-functional teams to ensure scalable, robust, and secure data science solutions aligned with business objectives.
Responsibilities
Architectural Design:
Design and develop the overall data science architecture, including data ingestion, storage, processing, and analytics frameworks.
Ensure the architecture supports scalability, performance, and security requirements.
Technology Leadership:
Stay abreast of emerging technologies and trends in data science, machine learning, and big data.
Evaluate and recommend new tools, technologies, and methodologies to enhance data science capabilities.
Collaboration:
Work closely with data scientists, engineers, and business stakeholders to understand requirements and translate them into technical solutions.
Foster a collaborative environment that encourages innovation and knowledge sharing.
Implementation & Deployment:
Oversee the implementation of data science projects from conception through deployment.
Ensure that solutions are deployed in a manner that is consistent with best practices and organizational standards.
Data Governance:
Establish and enforce data governance policies and standards to ensure data quality, integrity, and compliance.
Mentorship & Training:
Mentor and guide junior data scientists and engineers, providing technical leadership and career development support.
Qualifications
Education:
Bachelor's or Master's. in Computer Science, Data Science, Statistics, or a related field.
Experience:
Minimum of 10 years of experience in data science, with at least 3-5 years in an architectural or leadership role.
Proven experience with designing and implementing large-scale data science solutions.
Technical Skills:
Strong proficiency in programming languages such as Python, R, and SQL.
Extensive experience with machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn).
Solid understanding of big data technologies (e.g., Hadoop, Spark, Kafka).
Experience with cloud platforms (e.g., AWS, Azure).
Soft Skills:
Excellent communication and interpersonal team management skills.
Strong problem-solving abilities and attention to detail.
Projects - TAIM, Vehicle Planning Chatbot, PIA, PMHero, AI Driven Testing
Architectural Design:
Design and develop the overall data science architecture, including data ingestion, storage, processing, and analytics frameworks.
Ensure the architecture supports scalability, performance, and security requirements.
Technology Leadership:
Stay abreast of emerging technologies and trends in data science, machine learning, and big data.
Evaluate and recommend new tools, technologies, and methodologies to enhance data science capabilities.
Collaboration:
Work closely with data scientists, engineers, and business stakeholders to understand requirements and translate them into technical solutions.
Foster a collaborative environment that encourages innovation and knowledge sharing.
Implementation & Deployment:
Oversee the implementation of data science projects from conception through deployment.
Ensure that solutions are deployed in a manner that is consistent with best practices and organizational standards.
Data Governance:
Establish and enforce data governance policies and standards to ensure data quality, integrity, and compliance.
Implement data security measures to protect sensitive information.
Mentorship & Training:
Mentor and guide junior data scientists and engineers, providing technical leadership and career development support.
Conduct training sessions and workshops to enhance team skills and knowledge.
Performance Monitoring:
Monitor the performance of data science solutions and implement improvements as necessary.
Education:
Bachelor's or Masters. in Computer Science, Data Science, Statistics, or a related field.
Experience:
Minimum of 10+ years of experience in data science, with at least 3-5 years in an architectural or leadership role.
Proven experience with designing and implementing large-scale data science solutions.
Skills Required
- Bachelor's or Master's in Computer Science, Data Science, Statistics, or related field
- 10+ years experience in data science with 3-5+ years in an architectural or leadership role
- Proven experience designing and implementing large-scale data science solutions
- Proficiency in Python, R, and SQL
- Experience with machine learning frameworks such as TensorFlow, PyTorch, Scikit-learn
- Experience with big data technologies such as Hadoop, Spark, and Kafka
- Experience with cloud platforms (AWS, Azure)
- Experience establishing and enforcing data governance, data quality, and security standards
- Proven leadership, mentoring, and communication skills
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