Required Candidate profile

We are looking for a Senior Data Scientist with a min of 10 years experience in Banking Financial Domain (especially Compliance related) and a solid background in Cloudera.

As a Cloudera Specialist, you must be adept in Cloudera tools like CDH, CEPH, CM, CMA, Data node EDH, HVE, JAS, NameNode, Nodemanager, QJM, QJN, RM and ZK.

This will be a two years assignment to one of the Leading Class A banks in Abu Dhabi.

Candidate should have finished two or three full implementations of Data Analytics in Compliance in large Enterprise Banks.

• Should be having thorough knowledge in R, Python, Scala on demand and Jupyter Notebooks.
• Should be having hands experience in CCA Spark and Hadoop developer.
• Should be having a Financial Compliance Background with a good knowledge and hands on expertise on Compliance related domains.
• Should be a Machine Learning expert and create new models and use various library in that area. You should have proven skills in this area.
• Should be having a thorough theoretical and practical idea on the following systems (From a Data Scientist Perspective)
• HDFS
• Yarn
• MapReduce
• Hive
• Pig
• Apache Ambari
• HBase / Apache Impala
• Storm
• Oozie
• Ranger
• Zookeeper
• Various data ingestion tools like Sqoop, flume, Kafka
• Various reporting tools like Drill, Phoenix, Zeppelin
• Will be an added advantage if you have exposure to GPU processing, Tensor Flow and Data Lakes.
• Should be able to produce high Quality Business documentation, Project Management, Agile Framework practices as needed.
• Should inspect the current Cloudera Architecture and suggest enhancements or improve it.
• Should be able to communicate with Senior Business Management ideas, concepts and deliverables.
• If you have certifications on Cloudera (Cloudera Data Engineer, Spark and Hadoop Developer), it will be an added advantage.

Data Scientist - Compliance

Responsibilities:

• Use advanced analytics methods to extract value from business data
• Perform large-scale experimentation and build data-driven models to answer business questions
• Conduct research on cutting-edge techniques and tools in machine learning/deep learning/artificial intelligence
• Determine requirements that will be used to train and evolve deep learning models and algorithms
• Articulate a vision and roadmap for the exploitation of data as a valued corporate asset
• Influence product teams through presentation of data-based recommendations
• Evangelize best practices to analytics and products teams
• Assemble large, complex data sets that meet functional / non-functional business requirements.
• Identify, design, and implement internal process improvements: automating manual processes, optimizing analytics delivery, re-designing infrastructure for greater scalability, etc.
• Build analytics tools that utilize the data to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics.
• Work with stakeholders including the Executive, Product, Data and Design teams to assist with analytics related technical issues and support their data infrastructure needs.
• Work with data and analytics experts to strive for greater functionality data systems

Typical skills and background:

SKILLS:

• Can work with data to identify patterns.
• Use judgement to form conclusions that may challenge conventional wisdom and focus on the crux of issues to identify high-leverage intervention points and strategies.
• Rapidly acquire new knowledge and learn new skills
• Seek to understand business needs and get results that have a clear, positive, and direct impact on business performance
• Apply different strategies to convince others to change their opinions or plans and ensure that proposals or arguments are supported by strong logic and a compelling business case, addressing all relevant factors.
• Consider the relative costs and benefits of potential actions to choose the most appropriate one
• Communication and storytelling
• Teamwork and collaboration
• Banking domain business knowledge
• Advanced analytics modelling and orchestration
• Solid development skills in Java, Scala and SQL
• Sound knowledge of using data science tools and languages like Cloudera Data Science Workbench (CDSW), Jupyter Notebook, Python etc.
• Clear hands-on mastery in big datab systems - Hadoop ecosystem, Cloud technologies (AWS, Azure, Google), in-memory database systems (HANA, Hazel cast, etc) and other database systems - traditional RDBMS (Terradata, SQL Server, Oracle), and NoSQL databases (Cassandra, MongoDB, DynamoDB)
• Comfortable in dashboard development (Tableau, Powerbi, Qlik, etc) and in developing data analytics models (R, Python, Spark)

EXPERIENCE AND QUALIFICATION:

• Masters degree from top-tier college/university in Computer Science, Statistics, Economics, or other closely-related field
• Minimum of 6 years' hands-on experience with a strong data background
• Extensive experience working with Big Data tools and building data solutions for advanced analytics
• Experience with statistical software, scripting languages, and packages (e.g. R, MATLAB, SAS, and Python)
• Considerable experience in solving business problems with advanced analytical solutions
• Proven experience in conducting statistical analysis and building models with advanced scripting language such as R, SPSS, or other analytic tools.
• Experience building and deploying predictive models, web scraping, and scalable data pipelines.
• Strong understanding of statistical methods and skills such as Bayesian Networks Inference, linear and non-linear regression, hierarchical, mixed models/multi-level modeling
• Practical knowledge across data extraction and transformation tools - traditional ETL tools (Informatica, Altryx) as well as more recent big data tools

Financial Renumeration will be based on your skills and expertise.

Notice Period of 30 to 45 days preferred

Previous working experience in Middle East and Gulf regions preferred Roles and Responsibilities

Desired Candidate Profile

Perks and Benefits