Lead Data Scientist
We are seeking a highly skilled Lead Data Scientist to lead the development and deployment of advanced Machine Learning solutions. This role involves influencing the technical direction of the team, collaborating closely with Product and Engineering partners, and driving innovation across data-driven initiatives.
This is an excellent opportunity for someone who combines strong technical expertise with leadership capabilities and a passion for building high-impact solutions. Key responsibilities include leading end-to-end development and deployment of Machine Learning models, writing clean efficient scalable code, analyzing large-scale datasets, applying state-of-the-art ML methodologies, mentoring junior scientists and engineers, and contributing to organizational technical leadership through patent filings and publications.
* Develop and deploy Machine Learning models to solve complex business problems.
* Write and maintain clean efficient scalable code following industry best practices.
* Analyze large-scale datasets to extract insights and support data-informed decision-making.
* Apply state-of-the-art ML methodologies including deep learning and modern frameworks to build robust models.
* Take ownership of key system components and influence the broader technical strategy.
* Collaborate with cross-functional stakeholders to design deployable production-ready ML solutions.
* Mentor junior scientists and engineers fostering team expertise and growth.
* Contribute to organizational technical leadership through patent filings and publications in top-tier venues.
Required Skills:
* 5+ years of industry experience in applied Machine Learning.
* Master’s degree or PhD in Computer Science Machine Learning Statistics Operations Research or a related field.
* 3+ years of experience building deploying and managing ML and deep learning models in production at scale.
* Deep understanding of ML best practices A/B testing pipelines feature engineering experiment design.
* Strong knowledge of algorithms and techniques such as gradient boosting deep neural networks transformers and optimization methods.
* Experience in Computer Vision; experience in Causal Inference is highly desirable.
* Expertise with Python scientific libraries (NumPy pandas Polars) and ML frameworks (PyTorch TensorFlow Keras Scikit-Learn).
* Strong data engineering skills and comfort working with large-scale datasets.
* Experience with big data tools (Apache Beam Kafka Spark).
* Experience with cloud platforms: AWS GCP or Azure.
* Fluency in Python and SQL.
Preferred Qualifications:
* PhD in CS ML AI Statistics OR or related fields.
* Experience applying ML to real-world retail industry problems.
* Familiarity with modern MLOps tools and pipelines.
* Impact-driven mindset and commitment to delivering high-quality models.
* Demonstrated leadership capabilities with experience guiding or managing technical teams.