AddressPosition Description : The Data & Analytics Practitioner role is an opportunity to be part of the technology practices at Iris. The candidate will also have the opportunity to collaborate with Client Partners at Iris to engage with Iris clients with practice presentations and technology solutions on Data Science and Analytics solutions. The successful candidate will have the opportunity to build competency of ML Ops, Data Science in Data & Analytics collaborating with Iris Practice Leaders and Delivery Heads.
Key Responsibilities :
- Senior professional level role with hands-on enterprise level architect with deep experience in ML Ops, Data Science and Advanced Analytics and on public cloud like AWS / Azure / GCP
- Focus on building practice competencies on ML Ops, Data Science and Advanced Analytics
- Engage with client managers with practice presentations, proposal responses and help Iris Sales team win solution engagements in Data and Analytics
- Rapidly architect, design, prototype, and implement architectures to address solutioning of ML Ops, Data Science and Advanced Analytics for a variety of Iris clients and prospects
- Build practice collateral case studies, Point of Views (PoVs) on Data Science and Advanced Analytics, etc.
- Assisting to train others on ML Ops, Data Science and Advanced Analytics related tools and technology.
- Staying up to date in the field regarding best practices, new and emerging tools, and trends in ML Ops, Data Science and Advanced Analytics
- Perform additional responsibilities or special projects as assigned by management.
Professional Experience / Qualifications :
- Bachelors degree / Masters degree in a Software discipline and/or MBA is a plus
- 12+ years of experience w.r.t. Data Science and Advanced Analytics
- Professional with a background in Data Science and Advanced Analytics, should have led multiple engagements in Data Science and Advanced Analytics in terms of solutioning, architecture and delivery.
- Should have excellent client interaction and presentation skills
- Excellent English communication both written and verbal
Technology :
- For the above skill areas, must have lifecycle experience on some of the tools such as AWS SageMaker / Dataiku / Vertex AI / Azure ML etc.
- Database experience and programming experience on Python/Java etc.
- 3+ years of work experience with applied statistics / statistical modelling (e.g., , correlation, regression, classification, clustering, forecasting, outlier, time series)
- 3+ years of hands-on experience with Python or other software development programming languages, with working experience with Natural Language Processing and Topic modeling, Classifiers, and Neural Networks.
Nice to Have :
Industry Experience :
- Required : Good experience and exposure in Financial Services Investment Banking, Investment Management
- Desirable Other : Insurance, Logistics
