Job Description

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