[Hiring] Senior Data Scientist @Parser Limited

Role Description

As a Senior Data Scientist at Parser, you will bridge the gap between commercial strategy and machine learning execution. You will take end-to-end ownership of predictive and optimization models from exploratory data analysis and feature engineering to AWS production deployment directly influencing core marketplace metrics, conversion rates, and revenue generation.

• Design, train, and validate predictive and optimization models utilizing classical ML, statistical modeling, and deep learning architectures.
• Own the end-to-end ML lifecycle on AWS (SageMaker, Lambda, ECS), implementing robust MLOps practices, CI/CD pipelines, and automated retraining workflows.
• Design and execute rigorous evaluation pipelines, A/B testing frameworks, and hypothesis testing to quantify model efficacy in production environments.
• Establish comprehensive model monitoring protocols to actively track data drift, concept drift, and system health post-deployment.
• Collaborate closely with software and platform engineering teams to optimize inference latency, throughput, and system scalability.
• Partner with Product, Commercial, and Strategy stakeholders to translate ambiguous commercial problems into actionable, high-impact data initiatives.
• Communicate complex quantitative findings and strategic trade-offs effectively to both technical peers and executive non-technical leaders.

Qualifications

• 4+ years of hands-on experience in Data Science or Advanced Analytics delivering measurable, production-grade business impact.
• Advanced proficiency in Python (Pandas, NumPy, Scikit-learn) and complex SQL querying, with practical experience using deep learning frameworks (PyTorch or TensorFlow).
• Demonstrated experience deploying, scaling, and maintaining machine learning workloads on AWS cloud infrastructure (SageMaker, ECS, Lambda).
• Solid theoretical and applied foundation in statistical inference, experimental design, and supervised/unsupervised machine learning methodologies.
• Exposure to Generative AI workflows, LLM orchestration, and advanced prompt engineering.
• Degree (Bachelor’s or higher) in Data Science, Computer Science, Mathematics, Statistics, or an equivalent quantitative discipline.

Requirements

• Hands-on experience with model interpretability and explainability frameworks (e.g., SHAP, LIME) within regulated or customer-facing environments.
• Prior working background in Computer Vision (CV) or Natural Language Processing (NLP).

Benefits

• The chance to join an organization with triple-digit growth that is changing the paradigm on how software products are built.
• The opportunity to be part of an amazing, multicultural community of tech experts.
• A highly competitive compensation package.
• Continuous learning and development support with access to cutting-edge AI/ML tools and platforms.