CBRE - Senior Principal Data Scientist

Position : Sr Principal Data Scientist

Locations : Hyderabad, Noida, Gurugram

Exp : 8-12 years

Primary Skills : Machine learning, Deep learning, EDA

Good to have : NLP

Data Scientist :

CBRE is looking for a data scientist that will help us discover the information hidden in vast amounts of data, and help us make smarter decisions to deliver even better products. Your primary focus will be in applying data mining techniques, doing statistical analysis, and building high quality prediction systems integrated with our products. Also, improve and extend the features used by our existing classifiers, extract information from PDF / other forms of data.

Responsibilities:

- Selecting features, building and optimizing classifiers using machine learning techniques

- Data mining using state-of-the-art methods

- Extending company's data with third party sources of information when needed

- Enhancing data collection procedures to include information that is relevant for building analytic systems

- Processing, cleansing, and verifying the integrity of data used for analysis

- Doing ad-hoc analysis and presenting results in a clear manner

- Creating automated anomaly detection systems and constant tracking of its performance

- Pre-processing data skills, skimming the data and able to quickly segment for initial analysis.

- Understanding and Presenting data in domain objects.

- Ability to understand the business process and correlate the data.

Skills and Qualifications:

- Excellent understanding of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Decision Forests, etc.

- Experience with common data science toolkits, such as R, Weka, NumPy, MatLab, etc excellence in at least one of these is highly desirable

- Excellent communication skills

- Experience with data visualization tools, such as D3.js, GGplot, etc.

- Proficiency in using query languages such as SQL, Hive, Pig

- Experience with NoSQL databases, such as MongoDB, Cassandra, HBase

- Applied statistics skills, such as distributions, statistical testing, regression, etc.

- Good scripting and programming skills

- Data-oriented personality