Senior Data Scientist

We are looking for a Senior Data Scientist to join our data team and help transform complex data into actionable insights that enable strategic decision-making. You’ll work at the intersection of machine learning, analytics, and business strategy and the associated technical and non-technical teams —helping to shape data-driven solutions and strategies that power our data products and production operations.

The main objective of this role will be to develop the data strategies across multiple platforms and sources, build and implement the required data solutions in order to feed production platform’s forecasting and visibility functionality.

As a senior member of the team, you’ll be self-motivated and be able to take ownership of projects, collaborate closely with stakeholders across product, engineering, and business to deliver data science solutions.

Qualifications:

Experience:

• Strong coding skills in Python, including libraries such as pandas, scikit-learn, TensorFlow, or PyTorch.
• Expert in Python and ML frameworks (PyTorch, TensorFlow, Sklearn), with experience across NLP, computer vision, and LLMs.
• Strong statistical and experimental design background, including A/B testing and causal inference.
• Experience working with SQL and large-scale datasets.
• Demonstrated ability to turn ambiguous business problems into structured data science projects and implement them to enable action in end state platforms
• Excellent communication skills and ability to present complex ideas to non-technical stakeholders.
• Experience with cloud platforms (AWS, GCP, Azure) and tools like Databricks, Snowflake, or BigQuery.

Desirable Skills:

• Familiarity with MLOps, model monitoring, and production deployment.
• Experience in a specific domain (e.g., marketing, operations, fraud, personalization, NLP) is a plus
• Hands-on experience with LLM stacks (e.g., Mistral, LangChain, Chroma, Hugging Face Transformers).
• Interest in staying current with AI trends and contributing to internal R&D or innovation initiatives.

Key Responsibilities:

• Work across and support a range of data use cases including analytics and data provisioning
• Lead the design, development, and deployment of data strategies, machine learning models and advanced analytics solutions to support recommendation and insight to production use cases
• Apply statistical techniques to extract insights and support data-driven decision-making.
• Work alongside data engineering in requirements for data pipelines and feature engineering
• Promote best practices in data science, model validation, documentation, and reproducibility.

Working Conditions:

• Full-time.
• Limited travel may be required depending on team needs.
• Flexibility to operate in a global organization.