AI ML Engineer

Position: AI ML Engineer

Location: Mississauga, Hybrid 3 days/week

Job Description:

Responsibilities:

• As part of the Global Reconciliation Utility (GRU) and Data Engineering team, this role will be responsible for development and implementation of GRU ML models strategies.

• Lead ideation, technical development, and launch of innovative AI ML models and ensure the design and usage adheres to the overall Citi’s architecture blueprint.

• Undertake preprocessing of structured and unstructured data

• Analyze substantial amounts of information to discover trends and patterns.

• Build predictive models and machine-learning algorithms.

• Combine models through ensemble modeling.

• Present information using data visualization techniques.

• Propose solutions and strategies to business challenges.

• Collaborate with engineering and operational teams to ensure ML Models success and integration.

• Provide in-depth analysis with interpretive thinking to define issues and develop innovative solutions.

• Define ML Models roadmaps and schedules in collaboration with technical and business teams.

• Facilitate the creation and maintenance of proper ML Models documentation.

• Foster strong relationships with key stakeholders and external partners to support ML Models development.

Qualifications:

• AI/ML Development and Big Data experience

• Expertise with data reconciliations, data quality, large data processing and controls

• Expertise leading large scale Enterprise Transformation initiatives with a clear track record of success.

• Ability to articulate intricacies of Technology Architecture

• Deep functional and technical experience in Capital Markets across Front Office, Middle Office, Operations, Risk & Finance.

• Demonstrated leadership, management, and development skills.

• Experience with predictive analytics using large and complex datasets.

• Enthusiastic about AI and ML optimizations and open-source technologies

Skills required:

• Strong problem-solving skills with an emphasis on ML Models development.

• Experience working with and creating data architectures.

• Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks.

• Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests, and proper usage, etc.) and experience with applications.

• Excellent written and verbal communication skills for coordinating across teams.

• A drive to learn and master innovative technologies and techniques.

• familiar with the following software/tools:

o Knowledge and experience in statistical and data mining techniques: GLM/Regression, Random Forest, Boosting, Trees, text mining etc.

o Experience querying databases and using statistical computer languages: R, Python, SQL.

o Experience using web services: Redshift, S3, Spark

o Experience creating and using advanced machine learning algorithms and statistics: regression, simulation, scenario analysis, modeling, clustering, decision trees, neural networks, etc.

o Experience with distributed data/computing tools: Map/Reduce, Hadoop, Hive, Spark, MySQL /

o Experience with BI tools: Tableau, QlikView.

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Thanks

Prashant Bansal

Raas infotek corporation

262 Chapman road, Suite 105A, Newark, DE-19702

Phone: 302-565-0188 Ext: 144,

Email: [email protected]

Website: raasinfotek.com