About the Role
- We are seeking a highly analytical and innovative Data Scientist to join our Artificial Intelligence (AI) team and play a pivotal role in shaping data-driven product capabilities. This role is mission-critical in converting complex data into actionable insights, optimizing AI models, and enabling the development of intelligent systems that drive business growth and user engagement.
- As a key contributor to our AI initiative, you will collaborate cross-functionally with AI Engineers, Product Owners, and Domain Experts to design, develop, and validate scalable AI solutions. You will bring rigor, structure, and creativity to solving high-impact problems using data science methodologies.
Key Responsibilities
Data Exploration & Modelling
- Extract, clean, and preprocess large-scale datasets from structured and unstructured sources Build, validate, and tune predictive and descriptive models using state-of-the-art algorithms Leverage statistical analysis, machine learning, and deep learning to solve real-world
- problems
Collaboration & Strategy
- Partner with engineering teams to integrate models into production environments Work with product and business stakeholders to define data-driven KPIs and success metrics Translate complex technical findings into business-friendly insights and visualizations
AI Lifecycle Contribution
- Contribute to all phases of the AI lifecycle: problem framing, data wrangling, modelling, evaluation, and deployment
- Maintain and improve data pipelines and ML workflows in collaboration with MLOps and engineering teams Continuous Innovation
- Stay abreast of the latest research and trends in AI/ML/Data Science
- Rapidly prototype experimental approaches and evaluate performance against benchmarks Promote best practices in data science and mentor junior data practitioners where applicable
Required Qualifications
- Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Mathematics, or a related field
- 3+ years of experience in data science or analytics roles, ideally within an AI-focused team
- Proficiency in Python, or similar languages for statistical analysis and model building
- Hands-on experience with ML frameworks (e.g., Scikit-learn, TensorFlow, PyTorch)
- Strong SQL skills and familiarity with big data platforms (e.g., Spark, Hadoop)
- Experience with data visualization tools such as Power BI, Tableau, or Plotly
- Solid understanding of statistical modeling, A/B testing, and predictive analytics
- Ability to simplify complex technical concepts for non-technical stakeholders
Preferred Skills (Nice to Have)
- Experience deploying ML models to production in cloud environments (AWS, Azure, GCP)
- Familiarity with MLOps practices and tools (e.g., MLflow, Kubeflow, DVC)
- Exposure to NLP, or reinforcement learning is a plus
- Knowledge of data governance, privacy, and ethical AI practices
