About Job

CTC Undisclosed Job Location Canada Experience 5 - 8 yrs

Description

We help each other and foster collaboration across roles and teams

We lift each other up. We know how to celebrate our successes and learn from our failures

All of our efforts center around delivering value to our customers

We always try to do the right thing for ourselves, for the product and for our customers

Key Responsibilities

Solve business and technical problems with robust and statistically sound use of rigorous scientific methodologies and creative use of algorithms using AI, machine learning and predictive modelling techniques.

Complete execution of the data science process. This may be carried out in a collaborative environment with product and engineering teams, but ranges from understanding business requirements, data discovery and extraction to model development and evaluation.

Be comfortable and proactive in an environment that combines well defined problem specifications with at times unpredictable situations carrying a significant number of technically and functional unknowns.

Exercise solid verbal, interpersonal and written communication skills to carefully document results and findings and share results with various stakeholders.

Be proficient with tools and techniques to effectively work remotely with a global team in multiple geographical locations.

Collaborate closely with other data scientists and engineering and product teams to deliver compelling intelligent features to customers.

Essential Skills & Experience:

An advanced degree in Computer Science, Physics, Engineering, Mathematics, or another relevant quantitative field.

Excellent understanding of the mathematical theory behind algorithms underlying common machine learning techniques for solving classification and regression problems in a supervised setting as well as approaches for unsupervised learning.

2-5 years of postgraduate experience in AI, machine learning, data mining, analytics and/or predictive modelling.

Real-world practical experience with machine learning algorithms for classification, regression, clustering, dimensionality reduction.

A proven track record in developing, innovating, and applying advanced algorithms to address practical problems and in building new analytical products of commercial value.

Practical experience in feature engineering, feature evaluation, feature selection, model interpretation and visualization.

Great 2-5 years experience in more than one of Python, Scala and Apache Spark.

Proficiency in using query languages such as SQL and its adaptations.

Experience with horizontally scalable data stores such as Hadoop and other NoSQL technologies such as Map Reduce, Spark, HBase, etc., and associated schemas.

Desired Experience:

A PhD degree in a quantitative Science or technical field.

Demonstrated experience in engaging and influencing business leaders in solution path design.

Experience with one or more of the DNN frameworks, including TensorFlow, MXNet, Theano, etc. and applications of such libraries to NLP problems.

Detailed Description and Job Requirements

Designs, develops and programs methods, processes, and systems to consolidate and analyze unstructured, diverse big data sources to generate actionable insights and solutions for client services and product enhancement.

Interacts with product and service teams to identify questions and issues for data analysis and experiments. Develops and codes software programs, algorithms and automated processes to cleanse, integrate and evaluate large datasets from multiple disparate sources. Identifies meaningful insights from large data and metadata sources; interprets and communicates insights and findings from analysis and experiments to product, service, and business managers.