Data Scientist / Machine Learning Engineer

Summary

OBJECTIVE
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Seeking a challenging position in the field of machine learning and data science, where I can leverage my passion
for learning and apply my interdisciplinary skills to solve complex problems and drive meaningful insights from data.

SUMMARY OF QUALIFICATIONS
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Data scientist with hands on experience in machine learning and statistical modeling in Python (2+ yrs)
Physicist with strong varied scientific background, having successfully worked in multiple disciplines (5+ yrs)
Working knowledge of digital signal processing and image processing in Python (1+ yrs)
Experience in cloud-computing with Amazon Web Services (S3), Docker, MySQL, Snowflake SQL, and Prefect (1 yr)

EDUCATION
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Ph.D., Physics, Northeastern University, Boston, MA, US

PROFESSIONAL EXPERIENCE
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Freelance Data Scientist and Machine Learning Specialist (2023-present)

Senior Data Scientist (2021-2022)
Anomaly-detection (for defect-detection of battery interior through digital signal- and image-processing)
Data engineering (pipelining, orchestration, and data ingestion to AWS/Snowflake)
Ad-hoc Projects (Physics-driven analysis, ML/DL, etc.)

Graduate Research Assistant, Northeastern University, Boston, MA (2017-2021)
Leading the ideation, design, and build of an AI-enabled smart color-detection/spectral-estimation tool

SELECTED PUBLICATIONS
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2022, Elsevier Materials Today
2019, IOP Machine Learning: Science and Technology
2019, ACS Applied Nano Materials

Expectations

Looking for the next opportunities as machine learning engineer or data scientist, only full-time positions. I have 4-5 years of experience working with data -- almost 2 years in the in the industry and the rest in academia. I have a PhD in Physics, with concentration in solid states/semiconductors, and I prefer to be in an industry segment in which my Physics knowledge has value, though it is not a hard requirement.

Employment Preferences
Academic Degree
Experience

Total Professional Experience

8 years

Startup Experience

2 years

Big-Tech Companies

no experience

Enterprise Experience

no experience
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