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Lead Data Science Architect

About Us: VivSoft is an emerging technology company specializing in Cloud, Enterprise DevSecOps, AI, and Digital Customer Experience to drive mission-enabling digital transformation. We build mission-focused, scalable solutions through a diverse team of strategists, engineers, and designers experienced in high-performance software and AI factory accelerators. As we innovate in the government contracting sector, we seek a motivated Business Development Trainee on a path to becoming a skilled Capture Manager. This role involves learning the government contracting lifecycle, leading capture efforts, and driving strategic growth through aligning our solutions with client needs.


Job Duties:
  • Design and Develop Data Science Architectures: Utilize Amazon Web Services (AWS), Azure, and Google Cloud Platform (GCP) to create scalable and high-performance data architectures for complex analytics and AI applications.
  • Define Technical Strategy for Data Science Projects: Focus on algorithmic efficiency and advanced data analysis using Python, R, TensorFlow, and PyTorch to drive project innovation.
  • Integrate Emerging Technologies: Utilize cutting-edge Artificial Intelligence (AI)/Machine Learning (ML) tools such as Large Language Models (LLMs) for sophisticated data analysis and to streamline DevOps processes.
  • Employ platforms like Amazon SageMaker for streamlined model development, ML flow for effective lifecycle management, and Apache Kafka for robust real-time data streaming.
  • Integrate these technologies into a robust AI/ML infrastructure to enhance workflow efficiency and support the development of more sophisticated and reliable statistical models and analytics.
  • Provide Technical Leadership and Mentorship: Guide data scientists in machine learning and predictive analytics, leveraging Python, R, and TensorFlow to enhance team capabilities and project outcomes.
  • Lead Data Pipeline and Algorithm Development: Direct the design and implementation of data pipelines, data modeling, feature engineering, and algorithm development for effective data management and innovative solutions.
  • Collaborate with Cross-Functional Teams: Develop cohesive data-driven solutions using cloud technologies and automation pipelines to meet complex business requirements.
  • Manage the Development Lifecycle: Oversee the entire process of data science projects, from conception to deployment, ensuring quality, efficiency, and reliability.
  • Develop Scalable Cloud Infrastructure: Focus on creating efficient and adaptable data infrastructure on AWS, Azure, and GCP to meet evolving project needs.
  • Develop Predictive Models and Machine Learning Algorithms: Direct the creation of models and algorithms for data-driven decision making using TensorFlow, PyTorch, and scikit-learn.
  • Apply Advanced Analytics Techniques: Utilize Tableau, Power BI, and SQL/Non-SQL databases for sophisticated data visualization and complex dataset management.
  • Communicate Technical Insights: Effectively convey complex technical concepts to diverse audiences, translating intricate ideas into clear, actionable insights.
  • Provide Expert Guidance in Data Science Solutions: Drive the creation of bespoke solutions using in-depth knowledge of cloud platforms and data science tools. Leverage expertise, akin to that demonstrated by certifications such as AWS Certified Machine Learning Specialty, Google Cloud Certified Professional Data Engineer, and AWS Certified Solutions Architect, to align solutions with specific business needs and objectives.


Job Requirements:
  • Master’s degree in computer science, Statistics, Mathematics, Data Science, Business Intelligence and Analytics, or a related field; and four years of experience in job offered, Sr. AI Engineer, AI Engineer, Lead Application Developer, Data Engineer, Full Stack Developer, Solutions Architect/Developer, or in a related data science or data developer field.
  • Experience in job other than offered job must include a minimum of two years of experience in AWS; Azure; GCP; Python; R; TensorFlow; PyTorch; scikit-learn; Tableau; Power BI; SQL and Non-SQL databases; integrating machine learning models into production systems; implementing automation pipelines; hands-on experience with machine learning, predictive modeling, and advanced analytics.
  • Following certificates are also required: a) AWS Certified Machine Learning – Specialty; 2) Google Cloud Certified Professional Data Engineer; 3) AWS Certified Solutions Architect – Associate.


Worksite:
  • VivSoft Technologies LLC, 13221 Woodland Park Rd Suite 310, Herndon, VA 2017, or other unanticipated client location across the U.S.
  • To Apply:                   Send resume to HR, VivSoft Technologies, Inc., 13221 Woodland Park Rd, Ste 310, Herndon, VA 20171 or Email to: recruiting @ vivsoft.io


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What You Should Know About Lead Data Science Architect, VivSoft Technologies

Join VivSoft, an innovative technology company at the forefront of Cloud, Enterprise DevSecOps, AI, and Digital Customer Experience, as a Lead Data Science Architect in Herndon, VA! We are on a mission to drive digital transformation with our diverse team of strategists, engineers, and designers. In this exciting role, you'll have the opportunity to design and develop high-performance data architectures using AWS, Azure, and GCP. You'll define the technical strategy for our data science projects, employing your expertise in Python, R, TensorFlow, and PyTorch to push the envelope on what’s possible in data analytics and machine learning. Collaboration is key: you’ll work closely with cross-functional teams ensuring that our solutions align with complex business requirements. Mentorship is a significant part of your role too, as you guide our data scientists in integrating advanced analytics techniques and robust machine learning models into our processes. Your expertise in sophisticated tools like Amazon SageMaker and Apache Kafka will shape our data pipeline and algorithm development, leading to more reliable statistical models. At VivSoft, we value your ability to communicate technical insights to different audiences, making intricate data concepts accessible and actionable. If you're passionate about creating scalable cloud infrastructure and driving project innovation, come and join us to leave your mark on the industry with transformative data solutions!

Frequently Asked Questions (FAQs) for Lead Data Science Architect Role at VivSoft Technologies
What responsibilities does the Lead Data Science Architect at VivSoft have?

The Lead Data Science Architect at VivSoft is responsible for designing and developing scalable data science architectures using AWS, Azure, and GCP. This role involves defining the technical strategy for data science projects, integrating emerging technologies in AI and ML, and mentoring data scientists to enhance project outcomes. You’ll also lead the development of data pipelines and predictive models, ensuring a robust infrastructure for effective data management.

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What qualifications do I need to become a Lead Data Science Architect at VivSoft?

To qualify for the Lead Data Science Architect position at VivSoft, you need a Master’s degree in computer science, Statistics, Mathematics, or a related field, along with four years of relevant experience. Additionally, you should have hands-on expertise in AWS, Azure, GCP, Python, R, TensorFlow, and more. Certifications such as AWS Certified Machine Learning – Specialty and Google Cloud Certified Professional Data Engineer are also required to support your application.

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What technologies are utilized by the Lead Data Science Architect at VivSoft?

At VivSoft, the Lead Data Science Architect utilizes a variety of cutting-edge technologies, including Amazon Web Services (AWS), Azure, Google Cloud Platform (GCP), Python, R, TensorFlow, and PyTorch. You will also work with tools like Amazon SageMaker for model development and Apache Kafka for real-time data streaming. Knowledge of data visualization tools like Tableau and Power BI are also crucial.

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How does the Lead Data Science Architect collaborate with other teams at VivSoft?

Collaboration is essential for the Lead Data Science Architect at VivSoft. This role requires working closely with cross-functional teams to develop cohesive, data-driven solutions that meet complex business needs. You will communicate technical insights effectively, ensuring different teams understand the implications of data science solutions and their applications in various projects.

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What is the career growth potential for a Lead Data Science Architect at VivSoft?

As a Lead Data Science Architect at VivSoft, you'll have significant career growth potential. The role not only allows you to lead innovative projects but also provides opportunities to mentor junior data scientists and steer strategic growth initiatives. Your expertise in advanced analytics and leadership within this dynamic company can open doors to higher leadership positions or specialized roles in advanced data solution development.

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Common Interview Questions for Lead Data Science Architect
Can you explain your experience with cloud platforms like AWS and GCP in the context of data science?

In answering this question, highlight specific projects where you utilized AWS or GCP for data architecture and analytics. Discuss services you used, such as AWS S3 for storage or GCP's BigQuery for large-scale data analytics, and elaborate on how these played a role in your data science projects.

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How do you define technical strategies for data science projects?

Describe your approach to developing technical strategies, emphasizing your analytical skills. Discuss how you assess project requirements, align them with available technologies, and iterate on your strategies based on project outcomes to maximize efficiency and effectiveness.

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What machine learning algorithms are you most comfortable with, and why?

Identify key algorithms you’ve implemented, such as decision trees, neural networks, or clustering methods. Explain your understanding of when to use each algorithm, highlighting specific case studies that led to successful outcomes.

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How do you ensure the data pipeline you design is efficient and scalable?

Discuss your process for designing data pipelines, mentioning your experience with tools like Apache Kafka for real-time streaming and batch processing solutions. Provide insights on how you monitor performance and adapt pipelines to changing project needs.

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Can you describe your experience mentoring junior team members in data science?

Share specific examples where you've guided junior data scientists. Describe the setting, topics covered, and any skills you encouraged them to develop. Highlight the impact of your mentorship on their performance and the team's success.

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What techniques do you use for data visualization, and why are they important?

Discuss your proficiency with tools like Tableau or Power BI, and explain the significance of effective data visualization in communicating complex insights. You might illustrate this by sharing a project where visualization played a key role in decision-making.

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How do you approach project management in data science?

Detail your project management approach, touching on methodologies you employ, such as Agile or Scrum. Share how you keep stakeholders informed and ensure projects stay aligned with business objectives while meeting deadlines.

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What is your experience with integrating machine learning models into production systems?

Discuss your hands-on experience in deploying models, including what platforms you used and the challenges you faced during integration. Mention the importance of scalability and efficiency in your deployment processes.

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What advanced analytics techniques are you familiar with, and how have you applied them in your work?

Talk about your experience with techniques such as predictive modeling or A/B testing. Provide examples of projects where these techniques helped in drawing actionable insights or business decisions, showcasing your analytical abilities.

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How do you stay updated with the latest developments in data science and AI?

Share your strategies for continued learning, whether through online courses, attending conferences, or following industry publications. Emphasize your commitment to staying relevant in a rapidly evolving field, which ultimately benefits your work as a Lead Data Science Architect.

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Full-time, on-site
DATE POSTED
December 5, 2024

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