Xpressbees - Data Scientist

Data Scientist must be a hands-on Statistician, who will develop and manage a world class team of data scientists that will drive customer engagement and business value by using data and advanced analytics. She/he will act as a thought leader for the use of data to drive critical business strategy and decisions.

Responsibilities:

- Develop and implement a strategic roadmap to progressively move towards an increasingly data driven organization

- Lead all data related activities to support development of new data science approaches and methodologies to improve operations and business outcomes

- Project management of multiple projects involving different stake holders.

- Partner with Business and Product in design, measurement and feedback loop for continuous improvement and deliver top notch analytical/data solution for logistics business

- Mentor and develop a team of data scientists

- Partner with academia and vendors to leverage cutting edge AI/ML solutions for the organizations

- Person would be required to work individually or as part of a team on data science projects and work closely with business partners across the organization

- He/she would be developing statistical/machine learning models using various techniques (supervised, unsupervised, semi-supervised) and technologies including but not limited to SAS, R, Python, Spark, H2O, Aster and various big data distributions like Hortonworks and MapR

Preference :

- Experience in using algorithmic techniques to solve some of the most analytically complex business problems, leveraging troves of raw information to figure out hidden insight that lies beneath the surface.

- Has used Big Data across devices( Hadoop, AWS,HDFS systems).

- Individuals having experience in building the large scale data sciences team (preferably mobile) from the scratch.

- Experience in designing and developing solutions across domains applying advanced machine learning techniques and Big Data technologies

Skills :

- Expertise in statistics, regression and classification models, machine learning techniques, NLP and Optimization techniques.

- Proven competencies in learning new products and services, new business, new verticals

- Experience in python, R or any other programming language for data science

- Experience working with big data and machine learning technologies

- Excellent command over supervised, unsupervised and semi-supervised techniques including but not limited to Random Forest, GBM, Ridge-Lasso-ElasticNet, ensemble learning (xgboost), Time-series techniques like Arima (and the family), Arch, Garch etc.

- Experience with Deep-learning, Artificial intelligence techniques like ANN, CNN, DNN, RNN etc. and how to strategize deep-learning layer and activations.

- Experience implementing machine learning algorithms such as support vector machines, decision trees, logistic regression, clustering, neural networks, graphical models etc.

- Excellent understanding of model metrics including AUC, ROC, CAP-curve, F-statistics etc. with clear understanding of how model performance is tuned

- NLP, Text mining, Image/Voice processing, digital analytics, deep learning, machine learning

- Consult with partners to define issues/information needs

- Working expertise in Tensorflow, Keras or Pytorch would be added advantage