WHAT YOU9LL DO:

• End to end ML development: Evaluate, implement, and improve machine learning techniques to solve real world problems and aid business decision making.

• Contribute extensively to the full model development lifecycle, from ideation, analysis, model creation and operation.

• Leverage large language models (LLMs) and RAG (retrieval augmented generation) frameworks to enhance data product reach and automate internal workflows.

• Write production-grade, clean, maintainable, and scalable code for running experiments and proofs-of-concept. Collaborate with Data Engineers to build robust data pipelines and deploy models.

• Monitor model drift and bias in production, ensuring our AI solutions remain ethical, accurate and high performing over time.

• Lead Experimental Design, A/B testing and causal inference projects to measure the direct impact of product changes and model performance.

• Translate model outputs into actionable business strategies for non-technical leadership, utilizing storytelling as a vehicle to make analytics & insight deliverables accessible and memorable.

• Perform ad hoc analysis to uncover business insights and opportunities, exploring data to discover patterns, meaningful relationships, anomalies, and trends across different formats and platforms.  

• Employ quick prototyping to gather feedback and adjust to user asks in an agile fashion.

• Follow best practices to build scalable enterprise BI and analytics solutions, ensuring data and reports are thoroughly tested before production release.

• Document objectives and solutions in summary as well as technical details.

• Collaborate with data and BI engineers, data product managers and business users to explore and create solutions for relevant business problems.

WHAT YOU9LL BRING:

• Proficiency with programming and data analysis using Python, Spark, and ML frameworks (NumPy, Pandas, Sci-kit Learn, XGBoost, TensorFlow, PyTorch).

• Strong mathematical foundation in statistics, probability, optimization algorithms, linear algebra and AI technologies.

• Working knowledge of statistical and machine learning techniques including classification, regression, clustering, and multivariate methods.

• Expertise with relational data modeling and advanced SQL for data manipulation and performance optimization.

• Experience working in an Agile/SCRUM environment

• Strong problem-solving, analytical, and communication skills (written, verbal, and interpersonal).

• Strong organizational skills, attention to detail, and ability to prioritize workload.

• Professional presence with ability to take initiative, be creative, curious, and collaborative in a flexible, team-oriented environment.

• Ability to independently conduct in-depth data analysis.

REQUIREMENTS:

• Bachelors/Masters/Ph.D. in quantitative field (Computer Science, Statistics, Mathematics, Physics) or equivalent industry experience.

• 3+ years in a professional data science role with proven track record of moving models from research to production

• 5+ years experience in professional data science role with advanced analytics applications preferred.

• Strong communication and presentation skills 6 ability to articulate technical challenges and solutions to diverse audiences.

• Familiarity with retail, supply chain, digital & financial analysis, predictive analytics, and BI visualization toolsets.

• Experience with DSML Automation platforms and MLOps tools.

• Experience with Data Engineering/Cloud tools (Snowflake, BigQuery, AWS SageMaker), GenAI tools (Hugging Face, LangChain, LlamaIndex, OpenAI/Gemini APIs), and cloud-based BI and Analytics technologies.

• Ability to work with minimal oversight while ensuring timely, accurate task completion.

Pay range for this position is $95.000 6 $130,000/year USD.