The Data Scientist Architect will take the lead in designing and implementing advanced analytics solutions that drive data-driven decision-making across the organization. This role involves creating scalable data architectures, developing machine learning models, and collaborating closely with cross-functional teams to integrate analytics initiatives into business operations. You will play a critical role in architecting data solutions that support innovative analytics at DeepSource Technologies.
Key Responsibilities:- Design and oversee the construction of robust data architectures and pipelines to support extensive data analysis and modeling.
- Lead the development of machine learning algorithms and predictive models tailored to enhance business outcomes.
- Collaborate with data engineers and other stakeholders to ensure seamless data integration and optimization of data processing workflows.
- Conduct exploratory data analysis to uncover insights and trends that inform strategic business initiatives.
- Translate complex analytical results into actionable insights for non-technical stakeholders.
- Establish best practices for data governance, model validation, and testing in analytics.
- Stay updated with the latest advancements in data science, machine learning, and artificial intelligence to drive innovation.
- Mentor and guide junior data scientists and analytics teams to foster a culture of continuous learning and improvement.
- Document analytics processes, methodologies, and findings for internal reference and reporting purposes.
Requirements:- Ph.D. or Master's degree in Computer Science, Data Science, Statistics, or related field.
- 7+ years of experience in data science, machine learning, and analytics roles, with at least 3 years in an architectural or leadership position.
- Strong expertise in designing and implementing data architectures and workflows for large datasets.
- Proficiency in machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, Scikit-learn).
- Strong programming skills in Python and experience with SQL and databases (e.g., PostgreSQL, NoSQL).
- Experience in cloud environments and tools (AWS, Azure, or Google Cloud).
- Ability to communicate complex concepts clearly to a broad audience.
- Strong analytical and problem-solving skills with a focus on results.
- Published research papers or significant contributions to open-source projects in the field of data science are a plus.
Benefits:- Health Insurance
- Social Insurance