Callis

Data Scientist

https://www.opentalent.in/callis

Software Engineer

Member since June 22, 2026

Key Strengths

Demonstrated proficiency in Python, a core language for Data Science.
Experience with Jupyter Notebook, essential for data exploration and model development.
Exposure to AI/ML frameworks (TensorFlow, PyTorch, Keras, OpenCV) through the 'AI-lab' project.
Experience with Docker, which is valuable for reproducible research and deployment in Data Science.
Projects like 'syft', 'syfthub', and 'local-rag' suggest an interest in data processing and potentially RAG systems, which aligns with modern data science applications.

Cultural & Operational Fit

Cultural Fit Analysis

The candidate's personal projects demonstrate a strong initiative and a passion for learning and building across various technologies. The diversity of projects, from bioinformatics to web components and AI labs, suggests adaptability and a broad technical curiosity. This aligns well with a culture that values continuous learning and cross-functional engagement. The focus on open-source-like projects (repositories) indicates a collaborative mindset.

Soft Skills & Operational Fit

Insufficient data to assess soft skills or operational fit. No psychometric test results or interview feedback provided.

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Projects

kalendly

December 30, 2025 – Present

A universal calendar scheduler component that works seamlessly across React, Vue, and React Native with full TypeScript support.

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syfthub

November 17, 2025 – Present

syfthub — repository

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syft-hub-sdk

August 12, 2025 – Present

syft-hub-sdk — repository

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local-rag

June 23, 2025 – December 9, 2025

local-rag — repository

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primer

April 26, 2025 – Present

Pre-install security interceptor for package managers.

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syft

August 15, 2024 – Present

syft — repository

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primer-action

January 22, 2023 – Present

primer-action — repository

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graphs

October 17, 2022 – December 26, 2023

graphs — repository

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krane

August 11, 2021 – February 2, 2025

AWS Scholarship Capstone Project - A light-weight bioinformatics package

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AI-lab

October 10, 2019 – September 23, 2019

:fire::whale2: This repository contains a docker image that I use to develop my artificial intelligence applications in an uncomplicated fashion. Python, TensorFlow, PyTorch, ONNX, Keras, OpenCV, TensorRT, Numpy, Jupyter notebook... :whale2::fire:

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Key Strengths

Demonstrated proficiency in Python, a core language for Data Science.
Experience with Jupyter Notebook, essential for data exploration and model development.
Exposure to AI/ML frameworks (TensorFlow, PyTorch, Keras, OpenCV) through the 'AI-lab' project.
Experience with Docker, which is valuable for reproducible research and deployment in Data Science.
Projects like 'syft', 'syfthub', and 'local-rag' suggest an interest in data processing and potentially RAG systems, which aligns with modern data science applications.

Cultural & Operational Fit

Cultural Fit Analysis

Soft Skills & Operational Fit

Insufficient data to assess soft skills or operational fit. No psychometric test results or interview feedback provided.

Callis

Key Strengths

Cultural & Operational Fit

Top Skills

Skills

Projects

Key Strengths

Cultural & Operational Fit