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Data Scientist (2 positions) At Planet4iT

Location: Toronto, Ontario

Job Description

Contract opportunity in the banking sector in Toronto, the Data Scientist is an
expert contributor with an in-depth understanding of how to apply evolving
tools and technology in analytics, with a curiosity for deriving insights out
of data and applying them to address issues and insights that require
monitoring for compliance. Accountabilities include:

> Develop solutions (hands-on programming) using advanced analytics and big
data platform to identify anomalous behaviors, suspicious transactions and
inappropriate practices. This requires experience in predictive and
self-adaptive modelling, machine learning and preferably AI solutions
development
> Apply NLP and text analytics to structure and analyze volumes of contextual
data
> Work with large datasets and distributed computing tools (e.g., Hadoop,
Hive, Python, Kafka, Spark) for analysis, data mining and modeling for both
structured and unstructured data formats
> Work with software/tech developers and data engineers to operationalize
models including integration with vendor solutions, when applicable
> Develop/apply model testing strategies to measure performance on an ongoing
basis
> Collaborate with business lines and other stakeholders to confirm alignment
on business requirements and architectural design
> Prepare detailed documentation to outline data sources, models and
algorithms used and develop
> Work with other data scientists on the team and share expertise on how to
optimize codes, work in an agile environment and help them determine the
analytics tools fit for each solution.

The successful applicants will have:

> University degree in relevant STEM discipline (Computer Sciences,
Electrical/Computer/Software Engineering, Mathematics, Statistics)
> Experience cleaning, transforming and visualizing large data sets working
with various data formats (e.g. unstructured logs, XML, JSON, flat files,
audio, image)
> Experience with Big Data ecosystem tools (e.g., Hive, Pig, Sqoop, Spark,
Kafka) and experience with NoSQL databases (e.g., Hbase, Cassandra, Druid)
> Production experience with experimental design, statistical analysis,
machine learning and predictive modeling (e.g., cross-sell, upsell, attrition,
acquisition and lookalike models)
> Experience with common machine Learning libraries in R, Python, Spark
> Experience with UNIX tools and shell scripting
> Solid SQL skills for querying relational databases (e.g., SQL Server, DB2,
MySQL)
> Experience using and implementing visualization tools like D3, Tableau or
Qlikview

To apply, please quote the job reference code # 642634