Data Scientist

Position Overview

This role is focused on promoting data-driven culture and expertise in Data & Machine Learning Engineering. The candidate will primarily work on Snowflake and Azure ecosystems, Qlik-based visualizations, and be adept with DevOps and ML operations methodologies. Familiarity with logistics domain is advantageous, though eagerness to acquire domain knowledge is imperative.

Key Responsibilities

• Lead the development and management of Data and ML engineering projects.
• Create and sustain data and machine learning pipelines using technologies like Snowflake and Azure.
• Develop insightful data visualizations leveraging Qlik tools.
• Facilitate seamless integration and operational deployment of ML models via DevOps and ML Ops workflows.
• Work closely with diverse teams to assess data requirements and provide actionable insights.
• Champion data-informed decision-making throughout the organization.
• Drive initiatives to enhance data literacy within the business unit.

Qualifications and Experience

• At least three years of comprehensive experience handling end-to-end data warehousing and management projects. Recent graduates from reputed institutes with strong aptitude in data science are also welcomed.
• Deep practical knowledge in designing and deploying solutions on Azure Data platform, Snowflake, SnowPark, ML Ops, and DevOps environments.
• Prior exposure to logistics and transportation domains including familiarity with related data standards is preferred.
• Certifications such as Agile, DAMA, or Azure add value.
• Ability to engage and collaborate effectively with both technical and non-technical stakeholders, coupled with a proactive, positive mindset.
• Exhibit strong teamwork, adaptability to change, and perseverance to realize objectives.
• Excellent communication skills to facilitate cross-functional collaboration.