A
Anurag Yadav
Data Analyst
Profile
About you
Summary
not added
Total work experience
5-7 yrs
I can work legally in
India
Availability
Immediately
Current work sector
Information Services(N/A)
Languages
English (US)(Competent)
New Delhi, Delhi, India
Education
Postgraduate Degree - Masters of Computer Science
Bhopal, Madhya Pradesh, India
Work experience
Not added
Workplace preferences
Ideal workplace
Co-workers
Office meetings
Flexible working hours
Speed of change
Work from home policy
Ideal job
Desired job title
Data Scientist
Position type
Permanent
Travel
None
Relocation
No
Kaggle profile
Not added
Skills
Personal data
For how many years have you been writing code and/or programming?
5 years
For how many years have you used machine learning methods?
1 year
Have you ever published any academic research (papers, preprints, conference proceedings, etc)?
No
Select the title most similar to your current role (or most recent title if retired)
Software Engineer
Select any activities that make up an important part of your role at work: (Select all that apply)
- Analyze, understand and visualize data to influence product or business decisions
- Build and/or run a machine learning service that operationally improves my product or workflows
Approximately how much money have you spent on machine learning and/or cloud computing services at home or at work in the past 5 years (approximate $USD)?
$0 ($USD)
Approximately how many times have you used a TPU (tensor processing unit)?
Never
What is the size of the company where you are employed?
250-999 employees
Approximately how many individuals are responsible for data science workloads at your place of business?
10-14
Technical skills
Programming languages
Python
SQL
C
C++
Java
Javascript
Bash
C#
PHP
ML algorithms
Linear or Logistic Regression
Decision Trees or Random Forests
Recurrent Neural Networks
ML frameworks
Scikit-learn
TensorFlow
Keras
PyTorch
Computer Vision Methods
General purpose image/video tools (PIL, cv2, skimage, etc)
Image segmentation methods (U-Net, Mask R-CNN, etc)
Natural Language Processing (NLP) Methods
Transformer language models - pre-training
Transformer language models - fine-tuning
Transformer language models - reinforcement learning from human feedback
Production-Grade ML
Deploying new models to production
AB testing
Model testing
ML OPS best practices
Industry experience
Finance and Banking
Fraud detection
Churn prediction
Other use cases
Technology and Information Services
Cloud computing
Data analytics
Development of new software and hardware solutions