Data Scientist – Python, GCP, Data Mining, Machine Learning, Computer Vision

Collaborate with data engineering teams to validate and test data pipelines and models during proof-of-concept and production phases.

Design and deploy generative AI solutions, integrating them into analytics and product development workflows.

Define and track model KPIs, ensuring ongoing validation, testing, and retraining of models to align with business objectives.

Create reusable and scalable solutions through clear documentation, process flows, logs, and clean, well-commented code.

Communicate findings through concise reports, data visualizations, and storytelling to both technical and non-technical stakeholders.

Present operationalized insights and provide strategic recommendations to business and executive-level stakeholders.

Apply best practices in statistical modeling, machine learning, generative AI, distributed computing, cloud-based AI, and performance optimization for production deployment.

QUALIFICATIONS

Bachelor’s degree in a quantitative discipline (e.g., Statistics, Mathematics, Computer Science, Engineering, Operations Research, or related field).

Relevant experience – in applied data science, machine learning, generative AI, or advanced analytics. Min 5+ yrs of relevance experience

Min 5+ yrs of relevance experience

Proven experience in building and launching moderate-to-large-scale analytics and AI projects into production.

Requirements:

Strong analytical skills and attention to detail.

Relevant experience – in applied data science, machine learning, generative AI, r advanced analytics.

Proven experience in building and launching moderate-t-large-scale analytics and AI projects int production.

Expertise with statistical techniques, machine learning or operations research and their application in business applications.

Expertise in Python, Pandas, SQL, data mining, Supervised Learning, Unsupervised Learning, Deep Learning, Computer Vision, experience with large scale agent/model implementations

Deep understanding f data management pipelines and experience in launching moderate scale advanced analytics projects in production at scale.

Demonstrated experience in Cloud-AI technologies and knowledge of environments both in Linux/Unix and Windows.

Experience implementing pen-source technologies and cloud services; with r without the use f enterprise data science platforms.

Solid oral and written communication skills, especially around analytical concepts and methods.

Ability to communicate data through a story framework t convey data-driven results t technical and non-technical audience.

Employee Type:

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