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Lead Data Scientist at SkipTheDishes
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Open to opportunities related to Data Science
Udacity
Nano Degree Program, Self-Driving Car Engineering
January 1, 2018 – January 1, 2018
University of Manitoba
Master of Science (M.Sc.), Biomedical Engineering
January 1, 2014 – January 1, 2017
Mohammad Ali Jinnah University
Master of Science (MS), Electrical and Electronics Engineering
January 1, 2011 – January 1, 2013
Mohammad Ali Jinnah University
Bachelor of Science (B.S.), Electrical and Electronics Engineering
January 1, 2006 – January 1, 2010
SkipTheDishes
Lead Data Scientist
October 1, 2023 – Present
SkipTheDishes
Senior Data Scientist
September 1, 2021 – October 1, 2023
SkipTheDishes
Data Scientist
August 1, 2017 – September 1, 2021
Figley Neuroimaging Lab
Graduate Research Assistant / Software Developer
September 1, 2014 – July 1, 2017
Winnipeg, Manitoba, Canada
Hamdard University
Visiting Lecturer
January 1, 2014 – June 1, 2014
Islamabad, Pakistan
Renzym Pvt Ltd
Researcher / Developer
August 1, 2013 – December 1, 2013
Islamabad, Pakistan
Capital University of Science & Technology (CUST)
Junior Lecturer
February 1, 2012 – July 1, 2013
Islamabad, Pakistan
Vision & Pattern Recognition (VISPRS)
Researcher / Developer
November 1, 2009 – November 1, 2011
Islamabad, Pakistan
An SVM based score fusion for accurate Iris Recognition System
September 1, 2012 – July 1, 2013
Support Vector Machine was implemented to increase the accuracy of Iris based Biometric System
Iris Recognition System using High-ended Instruction sets of DSP kit
September 1, 2009 – August 1, 2010
1. Algorithm Development Phase in MATLAB A robust algorithm was developed for Iris Recognition System containing following steps: a) Segmentation of the iris boundary by using integrodifferential operator (IDO). b) Extraction of the Iris region. c) Reflection Removal from the Iris Region. d) Upper and lower Eyelid Removal from the Iris Region. e) Enhancement of the Image. f) Encoding of the Iris Region. 2. Implementation in C/C++: This algorithm was then implemented in C/C++ to make it platform independent. Different techniques were used to optimize the code within 1 second. 3. Matching Unit: The Encoding process is only done once, whereas, the matching process is performed millions of time. Use of PC for this purpose makes the process slow. A hardware accelerator is used for this purpose to achieve thousands of matches per second. The matching Unit was implemented on DSP Board TMS320DM6467 DVEVM and 80 thousand matches per second were achieved successfully.
Cultural Fit Analysis
The candidate's diverse background in academia (lecturer roles) and industry (researcher, data scientist) suggests adaptability. Their work on personal projects like Iris Recognition Systems demonstrates initiative and a passion for complex problem-solving. The progression within a single company (SkipTheDishes) indicates loyalty and growth potential. However, the projects listed are heavily focused on image processing and biometrics, which, while demonstrating strong analytical skills, may require a pivot to more traditional data analysis domains depending on the specific cultural needs of the target role.
Soft Skills & Operational Fit
The candidate's career progression from Data Scientist to Lead Data Scientist suggests leadership potential, problem-solving abilities, and a capacity for continuous learning. Their research background indicates strong analytical thinking and attention to detail. However, without psychometric test results, specific soft skills like teamwork, stress handling, and work attitude cannot be objectively assessed.