Data Scientist

Descriptions

You will be joining Azira, a global Consumer Insights platform, helping marketing and operational leaders improve their effectiveness with actionable intelligence to drive business results. Its mission is to create a more relevant world where brands are empowered to reach and build relationships with their consumers.

We are looking for a Data Scientist to join our growing team, working on cutting-edge analytics and machine learning solutions. This role is not just about research it is about delivering business value. The ideal candidate will have experience moving from research to production, ensuring that data science solutions drive measurable impact. You will be responsible for developing models, deploying them at scale, and ensuring they deliver tangible results aligned with business milestones. This role reports to Head of Data Science.

A Day in the Life

• Design and develop machine learning models (regression, classification, neural networks) that directly impact business outcomes.
• Work with large-scale datasets using big data tools such as Spark to generate actionable insights.
• Translate research into production-ready solutions, ensuring scalability, reliability, and performance.
• Deliver projects against defined business milestones, tracking progress and ensuring successful deployment.
• Optimize SQL queries to analyze structured data within cloud data storage environments.
• Implement data science solutions using Python and apply object-oriented programming (OOP) principles where necessary.
• Utilize cloud computing frameworks (preferably AWS, but experience with GCP or Azure is acceptable) to deploy and manage machine learning workflows.
• Collaborate with cross-functional teams, including engineers, business analysts, and product managers, to integrate models into production systems.
• Clearly communicate insights, technical solutions, and project progress to both technical and non-technical stakeholders.

What You Bring to the Role

• Experience: 3-4 years overall, with at least 1-2 years in a big data/analytics company.
• Strong foundation in statistics and probability for data analysis and model evaluation.
• Hands-on experience with regression, classification, and neural network models in real-world applications.
• Proven ability to transition from research to production, ensuring ML models deliver business impact.
• Experience delivering projects on time and aligned with business milestones.
• Proficiency in SQL for data extraction and manipulation within cloud data storage environments.
• Experience with cloud computing frameworks, preferably AWS (GCP or Azure also acceptable).
• Solid knowledge of Python programming and basic object-oriented programming (OOP) concepts.
• Experience working with big data tools like Spark for distributed data processing.
• A data science professional aligns data initiatives with business goals, communicates insights effectively, solves problems creatively, and collaborates with cross-functional teams.

Nice-to-Have Qualifications:

• Experience with MLOps frameworks, such as MLflow, for managing machine learning lifecycles.
• Proficiency in R programming language for statistical analysis.
• Understanding of CI/CD pipelines for machine learning deployment.
• Domain knowledge of geospatial datasets and mobility data.
• Experience with time series analysis for forecasting and trend detection.
• Basic understanding of LLMs (Large Language Models) and Generative AI.