Data Science (Python)

Required:

8+ years of experience 

Must: Python, Pandas, Numpy, sklearn, Pytorch/Tensorflow

Strong in: ML Algorithms, Deep learning algorithms, Able to fine-tune deep learning algorithms

Experience in : tabular data processing and EDA. Seaborn, matplotlib etc, any cloud platform

Desirable: Worked in "Anomaly detection" use cases, GCP

·      Proficient in Python and able to solve complex problems.

Solid understanding Al/ML/DL algorithms and related statistics. (e.g. regression, classification, clustering, unsupervised algorithms)

Able to build models and experiment with state of art fine techniques to improve model performance.

·      4+ years of experience in Design develop and deploy machine learning and deep learning models with strong experience in Python development with NumPy, Pandas, Scikit learn, Tensorflow/Pytorch etc

·      Experience of handling structured/unstructured data, Preprocess, analyse and visualize large datasets using python libraries like pandas, plotly, matplotlib, seaborn etc.

·      Conduct thorough data analysis feature engineering and model selection to ensure optimal model performance.

·      Collaborate with data engineers to integrate models into production system.

·      Conduct research and stay updated to propose innovative solutions and able to document model development processes, performance metrices and findings

·      Implement and optimize machine learning algorithms for real-time and batch processing

·      Strong understanding and experience working with machine learning algorithms including supervised and unsupervised learning

·      Familiarity with NLP or generative Al techniques (e.g. GANs, LLMs)

·      Experience with any public cloud platforms and familiarity with Cloud Run SQL and other GCP or other equivalent cloud services will be a plus