Role: Data Scientist
Location: Remote, however travel might be required as per business requirements
FTE Only
Where youโre headed
Youโll creatively use data to solve business challenges, often uncovering new and transformative opportunities along the way. Applying advanced analytics, quantitative tools, and modeling techniques, youโll interpret and offer recommendations based on insights from the data.
Where youโve been
Youโre a problem solver, data expert, analyst, and communicator, who can create new algorithms from scratch. You have an advanced degree in a quantitative field, such as computer science, engineering, physics, statistics or applied mathematics, and have:
Job Description:
- Familiarity with statistical techniques, data mining, hypothesis testing, and exploratory data analysis
- Strong knowledge of programming languages with a focus on machine learning and advanced analytics (such as Python, R, Scala)
- Experience working with large datasets, data pipelines, and relational databases
- A collaborative mindset with the ability to communicate complex analytical concepts effectively to both technical and nonโtechnical stakeholders
- Excellent problemโsolving skills with the ability to analyze issues, identify root causes, and recommend solutions quickly
- Proven experience building, validating, and deploying machine learning models endโtoโend in production environmentsย
- Strong understanding of model performance evaluation, experiment design, and model lifecycle managementย
- Ability to translate business problems into analytical frameworks and measurable success metricsย
- Experience working crossโfunctionally with engineering, product, and business teams to deliver impact at scale
ย
Good to Have:
- Experience with Generative AI, including large language models (LLMs), prompt engineering, fineโtuning, and retrievalโaugmented generation (RAG)ย
- Exposure to Agentic AI concepts, such as autonomous agents, tool usage, planning, memory, and multiโagent workflowsย
- Familiarityย with modern ML/AI frameworks (e.g., PyTorch, TensorFlow) and MLOps tools for deployment and monitoringย
- Experience deploying AI solutions on cloud platforms (Azure, AWS, or GCP) with an understanding of scalability and cost considerationsย
- Knowledge of responsible AI practices, including model explainability, bias mitigation, and governance