Lead Data Scientist - Deep learning

We are hiring for a global leader in outcome-based marketing, a global company with over 8,000 employees in over 40 offices around the world.

The company's award-winning data and technology is rooted in privacy by design and underpinned by powerful AI. With more than 50 years of experience in personalization and performance working with the world's top brands, agencies and publishers, they are a trusted partner leading CRM, digital media, loyalty and email programs.

Job description

- Contribute and build an internal product library that is focused on solving business problems related to prediction & recommendation.

- Research unfamiliar methodologies, techniques to fine tune existing models in the product suite and, recommend better solutions and/or technologies.

- Improve features of the analytics product to include newer machine learning algorithms in the likes of product recommendation, real time predictions, fraud detection, offer personalization etc

- Collaborate with client teams to on-board data, build models and score predictions.

- Participate in building automations and standalone applications around machine learning algorithms to enable a - One Click- solution to getting predictions and recommendations.

- Analyze large datasets, perform data wrangling operations, apply statistical treatments to filter and fine tune input data, engineer new features and eventually aid the process of building machine learning models.

- Run test cases to tune existing models for performance, check criteria and define thresholds for success by scaling the input data to multifold.

- Demonstrate a basic understanding of different machine learning concepts such as Regression, Matrix Factorization, K-fold Validations and different algorithms such as Decision Trees, Random Forrest, K-means clustering.

Skill&Experience :

- Bachelor's degree in a quantitative discipline (e.g., Statistics, Economics, Mathematics, Marketing Analytics) or significant relevant coursework

- Proficiency with a deep learning framework such as TensorFlow or Keras; minimum 1 years of experience

- Exposure to CNN, RNN neural networks based professional projects solving problem in the likes of time series data and image data.

- In-depth understanding of LSTM concepts and be able to implement advances techniques such as stacked, bidirectional and seq2seq

- Demonstrated proficiency in PYTHON and BIG DATA technologies and the proven ability to program in big data/cloud technologies such as AWS & SPARK; minimum 2 years of experience

- A Deep understanding of Recommender Systems and applications around real-time predictions

- Experienced with machine learning algorithms such as logistic regression, random forest, XG boost, KNN, SVM, neural network, linear regression, lasso regression and k-means.

- Knowledge and understanding of AWS Sagemaker

- Working experience in CI/CD tools such as GIT & BitBucket