Credit Risk Machine learning Modeler

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.

Compensation: $140,000.00 - $160,000.00 per year

About

In the perfect storm of technology forces shaping the business world, the question is not whether companies need to adapt to stay competitive but which tech partner to trust for long-term business improvement and transformation needs.

That's why iShare was founded: to be that credible IT partner that cuts through the buzzword clutter to deliver real value by real people. And that starts with doing the basics right.

Who We Are

Based in New Jersey, iShare is a boutique IT consulting firm with strategic advisory, development, and staffing services designed for specific industry verticals. iShare was founded to fill a real market need - with so much noise about cloud, big data, and information security, companies today are adopting software product after product and losing sight of which they need and why, while what they really need is credible consulting that takes the time to understand their company's unique scenario and requirement, and then architect a solution accordingly.

Recognizing this gap, senior industry executives put their credibility on the line to form iShare and ensure they create a fulfilling experience with lasting value for all stakeholders - customers, employees and partners. iShare leadership team has 20+ years average IT experience and is well-rounded in technology, operations, account and customer management. Our experience spans C-Suite positions with Fortune 100 firms as well as mid-tier firms. Our background includes stints at multibillion-dollar ITO / BPO firms as well as startups.