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Staff Software Engineer at Google DeepMind
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Assessing your cultural and operational fit
Research engineer with experience in machine learning, computer vision and robotics. Passionate about building optimised software, taking research into production code, collecting data and conducting experiments to verify effectiveness of models and writing reports on analysis to communicate effectively and clearly on results. I also try to use my skills to help the environment, working with conservation groups to apply deep learning methods in the field.
UCL
MSc, Dept. of Computer Science, Data Science and Machine Learning
January 1, 2015 – January 1, 2016
Jadavpur University, Kolkata
Bachelor’s Degree, Information Technology
January 1, 2007 – January 1, 2011
Google DeepMind
Staff Software Engineer
April 1, 2026 – April 1, 2026
London Area, United Kingdom
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Development Associate
July 1, 2011 – March 1, 2012
Bangalore
Introduction to Machine Learning in Production
Coursera
June 24, 2026 – Present
Neural Networks and Deep Learning
Coursera
June 24, 2026 – Present
The Data Scientist’s Toolbox
Coursera
June 24, 2026 – Present
Structuring Machine Learning Projects
Coursera
June 24, 2026 – Present
NETTECH Linux network administration and ethical hacking certification
United Latino Students Association
June 24, 2026 – Present
Convolutional Neural Networks
Coursera
June 24, 2026 – Present
Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization
Coursera
June 24, 2026 – Present
Cultural Fit Analysis
The candidate has a strong background in research and development within AI/ML, working for innovative companies. While their experience is heavily skewed towards Machine Learning and Software Engineering, their early career roles and Master's degree in Data Science and Machine Learning, along with a Data Analytics Intern role, suggest a foundational understanding of data analysis. However, the target role is 'Data Analyst', which might be a slight mismatch given their senior-level ML/SWE experience. Their project diversity is high within the ML domain, but less so in pure data analysis. The cultural fit is moderate, as their advanced ML background could be an asset, but their primary focus has shifted from core data analysis.
Soft Skills & Operational Fit
The candidate's resume indicates strong problem-solving skills through their work on complex ML problems and system design. Experience in translating business requirements to technical solutions and informing marketing departments suggests good communication and strategic thinking. Their diverse project experience implies adaptability and a collaborative mindset, crucial for operational fit.