Flexon Technologies Inc.

Sr. Data Scientist

⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Sr. Data Scientist in Cupertino, CA, on a long-term contract, requiring 8+ years of experience, advanced Python skills, and expertise in ML and Generative AI. Ex-Apple employees preferred. Day 1 onsite work is mandatory.
🌎 - Country
United States
πŸ’± - Currency
$ USD
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πŸ’° - Day rate
Unknown
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πŸ—“οΈ - Date
April 23, 2026
πŸ•’ - Duration
Unknown
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🏝️ - Location
On-site
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πŸ“„ - Contract
Unknown
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πŸ”’ - Security
Unknown
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πŸ“ - Location detailed
Cupertino, CA
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🧠 - Skills detailed
#Scala #Classification #Data Science #SciPy #Deployment #ML (Machine Learning) #Regression #Programming #Python #AI (Artificial Intelligence) #NumPy #"ETL (Extract #Transform #Load)" #Model Deployment #Pandas #Libraries #Data Extraction
Role description
Hi Hope you're doing great, This is Nishanth from Flexon Technologies, and I have a suitable role for you so please go through it and let me know your thoughts. Job Title: Sr. Data Scientist (Ex-Apple) Location: Cupertino, CA (Day1 Onsite) Duration: Long Term Contract Need Ex-Apple Employee. Job Description: About the Role: We are looking for a Senior Data Scientist to join our team and play a pivotal role in designing, building, and deploying scalable data solutions, responsible for the end-to-end data science lifecycleβ€”from initial problem definition and data extraction to model deployment. The ideal candidate is as comfortable writing production-level code as they are applying advanced statistical methods and modern Generative AI techniques to solve complex business problems. Experience Required: β€’ Experience: 8+ years of relevant industry experience working on complex, data-driven projects. β€’ Technical Stack: Advanced proficiency in Python and industry-standard libraries (Pandas, NumPy, SciPy, Scikit-Learn, etc.). β€’ Engineering Mindset: Strong understanding of OOP and software engineering principles in a production environment. β€’ Model Expertise: Proven experience in both traditional ML algorithms (Regression/Classification) and modern Generative AI technologies (LLMs, RAG). β€’ Communication: Ability to distill technical findings into clear, impactful presentations for stakeholders. Key Responsibilities: β€’ Lead data projects through every stage of the lifecycle: definition, collection, preparation, modeling, and deployment. β€’ Architecture & Engineering: Apply rigorous Object-Oriented Programming (OOP) concepts and scalable software design principles to ensure code quality and system performance. β€’ AI & Machine Learning: Design and implement robust models, including traditional classification and regression algorithms, as well as cutting-edge GenAI, LLMs, and RAG (Retrieval-Augmented Generation) pipelines. β€’ Drive best practices in model development and evaluation to ensure accuracy and impact.