Overview:
As a Data Scientist, you will play a key role in developing and deploying machine learning models that drive business decisions and enhance customer experiences. You will collaborate with data scientists, data engineers, and business stakeholders to design and implement scalable solutions that optimize operations across areas such as product design, supply chain, retail, and marketing.
This role focuses on building advanced capabilities in personalization, forecasting, and Generative AI to deliver innovative, data-driven outcomes. You will work in a global, cross-functional environment where creativity, technical excellence, and collaboration are highly valued.
We are seeking a data professional with strong technical expertise, hands-on experience in productionizing models, and the ability to translate analytical insights into impactful business solutions.
Responsibilities:
- Model Development: Lead the design, development, and deployment of end-to-end machine learning solutionsfrom exploration and prototyping to implementation and performance monitoring.
- Data Exploration and Analysis: Conduct in-depth data analysis to understand data quality, distributions, and limitations for modeling purposes.
- Model Deployment: Implement and operationalize machine learning models in production environments, ensuring scalability, reliability, and maintainability.
- Stakeholder Collaboration: Partner with business stakeholders to identify opportunities for applying machine learning, understand business challenges, and translate them into analytical solutions.
- Performance Optimization: Continuously monitor and refine deployed models to improve accuracy, efficiency, and business relevance.
- Innovation & Research: Stay abreast of the latest trends and advancements in data science and AI, and integrate new methodologies to enhance model performance and productivity.
- Documentation: Maintain comprehensive documentation of models, code, and processes to support transparency, reproducibility, and team collaboration.
- Cross-Functional Collaboration: Work closely with data engineers, MLOps specialists, and business teams to identify relevant data sources and ensure smooth integration of machine learning solutions.
Requirements:
- Education:
- Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Applied Mathematics, or a related field.
- Experience:
- Minimum 5 years of experience as a Data Scientist, ideally in a fast-paced environment such as retail, e-commerce, or technology.
- Proven experience in developing, deploying, and maintaining machine learning models in production settings.
- Background in applying predictive analytics or AI to real-world business problems.
- Technical Skills:
- Proficiency in Python or R for data analysis and model development.
- Experience with machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn.
- Strong command of SQL and data manipulation techniques.
- Familiarity with data visualization tools (e.g., Tableau, Power BI, Matplotlib) and cloud platforms (AWS, Azure, or Google Cloud).
- Knowledge of big data technologies such as Hadoop, Spark, Databricks, or Snowflake is an advantage.
- Experience in ML systems design, development, and deployment using modern software development practices.
- Soft Skills:
- Excellent analytical and problem-solving abilities with a data-driven mindset.
- Strong communication skills, capable of translating complex analytical findings into actionable insights.
- Collaborative team player who thrives in cross-functional environments.
- Proactive learner with a passion for innovation and continuous improvement in the field of data science.
