Must Have -
- At least 8-10 years of experience in data analytics and data science
- Experience in credit risk analytics will be preferred
- Extensive knowledge of building machine learning models from scratch. At least 6+ years experience with special emphasis on the advanced algorithms like bagging, gradient boosting machines, random forests, SVM, K-means, deep learning or reinforcement learning
Role & Responsibilities Overview :
We are looking for analytics professional to lead a modeling team for a client in BFSI domain. You will be responsible for overseeing insights delivery, growth, and expansion of EXL within this engagement.
You will also collaborate with senior leaders and stakeholders to align & implement roadmap of modeling focused initiatives.
As an engagement lead, you will have the following responsibilities :
- End to end leading a team of data scientists. Provide project, client & team management and monitor progress of deliverables on daily basis and ensures timely resolution of any issues
- Provide technical direction on day to day basis to team of data scientists on data handling, data manipulation, predictive modeling spanning across stages of model development and implementation lifecycle.
- Serve as the functional and domain expert for the modeling team to ensure that they meet client expectations
- Understand the client’s business requirements, translate into a business problem and design the methodology to solve the business problem
- Expertise in machine learning model development and sound exposure on ML ops process
- Able to work in dual shore engagement across multiple time zones and must have experience in managing clients directly
- Stay updated on the latest trends and developments in machine learning model development techniques
- Facilitate client working sessions and lead recurring project status meetings
- Capability development identify and productize analytical solutions that can be implemented by different clients
Candidate Profile :
- Bachelor’s degree or higher in statistics, mathematics, computer science, or a related field
- At least 8-10 years of experience in data analytics and data science
- Experience in credit risk analytics will be preferred
- Extensive knowledge of building machine learning models from scratch. At least 6+ years experience with special emphasis on the advanced algorithms like bagging, gradient boosting machines, random forests, SVM, K-means, deep learning or reinforcement learning
- Proficiency in manipulating large scale data using Python and SQL
- Knowledge of MS Azure / AWS services or similar cloud platforms
- Sound understanding of ML ops process
- Proven track record of leading and managing analytics teams and projects
- Excellent communication, presentation, and interpersonal skills
- Ability to work independently and collaboratively in a fast-paced and dynamic environment
Flexible work from home options available.
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