A
Abhimanyu Bhadauria
Data Science Intern
Profile
About you
Summary
Data Science and Business Analytics graduate skilled in Python, SQL, and machine learning, with strong
problem-solving and communication skills. Available from February 2025 to drive impactful, data-informed decisions.
Total work experience
1-3 yrs
I can work legally in
France, India
Availability
2 month
Current work sector
Sales & Marketing(N/A)
Languages
English (US)(Fluent), French(Basic)
Paris, Île-de-France, France
Education
Postgraduate Degree - Masters of Data Sceiences and Business Analytics, ESSEC Business School & CentraleSupelec
Paris, Île-de-France, France
3 or 4 yr. Undergraduate degree of Computer Science and Engineering, SRM Institute of Science and Technology
Chennai, Tamil Nādu, India
Work experience
Data Science Intern, Pernod Ricard
2024 - Present
Reseach Member, Bouygues Construction
2024 - 2024
Data Analyst Intern, Saran India
2021 - 2022
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
25%
Relocation
Yes
Kaggle profile
Followers
4
Medals
none yet
none yet Medalsnone yet
none yet Medalsnone yet
none yet Medals2
2Skills
Personal data
For how many years have you been writing code and/or programming?
4 years
For how many years have you used machine learning methods?
4 years
Select the title most similar to your current role (or most recent title if retired)
Data Scientist
Select any activities that make up an important part of your role at work: (Select all that apply)
- Experimentation and iteration to improve existing ML models
- Analyze, understand and visualize data to influence product or business decisions
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)?
$100-$999
Approximately how many times have you used a TPU (tensor processing unit)?
6-25 times
What is the size of the company where you are employed?
1000-9,999 employees
Approximately how many individuals are responsible for data science workloads at your place of business?
20+
Technical skills
Programming languages
Python
R
SQL
C
C++
Javascript
MATLAB
CUDA
ML algorithms
Linear or Logistic Regression
Decision Trees or Random Forests
Gradient Boosting Machines (xgboost, lightgbm, etc)
Bayesian Approaches
Evolutionary Approaches
Convolutional Neural Networks
Generative Adversarial Networks
Recurrent Neural Networks
Transformer Networks (BERT, gpt-3, etc)
Graph Neural Networks
ML frameworks
Scikit-learn
TensorFlow
Keras
PyTorch
Xgboost
Huggingface
Computer Vision Methods
General purpose image/video tools (PIL, cv2, skimage, etc)
Image segmentation methods (U-Net, Mask R-CNN, etc)
Object detection methods (YOLOv6, RetinaNet, etc)
Image classification and other general purpose networks
(VGG, Inception, ResNet, ResNeXt, NASNet, EfficientNet, etc)
(VGG, Inception, ResNet, ResNeXt, NASNet, EfficientNet, etc)
Generative Networks (GAN, VAE, etc)
Natural Language Processing (NLP) Methods
Transformer language models (GPT-3, BERT, XLnet, etc) - General
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
Monitoring
Model testing
Handling of incidents in production
Investigation of production incidents and Root Cause Analysis
ML OPS best practices
Feedback discussions with end users of the ML systems
Industry experience
Finance and Banking
Fraud detection
Credit scoring
Customer service automation
Technology and Information Services
Advancements in algorithms
Cloud computing
Data analytics
Retail and E-commerce
Personalized shopping experiences
Inventory management
Recommendation systems
Manufacturing and Industrial Automation
Predictive maintenance
Energy and Utilities
Energy demand forecasting
Education
AI-generated (e.g. LLM) content detection
Marketing and Advertising
Targeted advertising
Customer segmentation
Sentiment analysis
Market trend analysis
Other use cases