Ai/ Ml Architect

At Data Dynamics, we take a holistic approach to managing the explosive growth of unstructured data We care about delivering storage optimization and data optimization. Our Unified Unstructured Data Management Platform is an industry leader in Unstructured Data Management and our journey has just begun.

With over 300 clients operating in 6 continents, we have an enormous amount of F1000 user feedback. Like our clients, we believe in the power of Analytics
- Empower clients with metadata-based analysis, movement, management and content awareness for all unstructured data assets
- Deliver on existing SLA’s while improving existing CAPEX and OPEX unstructured data budgets
- Eliminate file type, storage or Cloud vendor lock-in with heterogeneous data movement, on-premise, on-premise to cloud or cloud to cloud
- Provide a NEW level of content insights to protect clients from unknown data exposure risks (GRC, PII, HIPAA, GDPR, etc.)

**Responsibilities**
- Deliver insightful presentations of analysis and business results to business unit leaders
- Develop analytics proof of concepts on emerging trends in different vertical areas to develop new analytical PoCs for Competency centre
- Evaluate and compare algorithm performance based on large, real-world data sets
- Work with product/business owners to map business requirements into products productized solutions and/or working prototypes of ML algorithms
- Leverage data to analyze the business unit function, identify the business drivers and recommend strategy and future course of actions
- Conceptualize modeling framework, define data requirement, create predictive variables and co-ordinate model implementation with other business partners, and create experimental designs to understand drivers of business performance.
- Hands on programming in Python, SAS and/or R
- Prior experience in writing model documents is strongly preferred but not required
- Timely training Analytics resources and sharing best practices with them

**Required Skills and Experience**
- Skilled in libraries such as Pytorch, Tensorflow, Sklearn, Numpy, Pandas, Matplotlib, for Data Visualization.
- Worked Independently for Deployment of Models using Dockers and Kubernetes in GCP, ML Flow, Azure, AWS, involving Model Scoring, Model Management, Model Drifting, Model Retraining Mechanisms.
- Conceptualize modelling framework, define data requirements, feature engineering & extraction, co-ordinate model implementation with other business partners, and create experimental designs to understand drivers of business performance.
- Deliver insightful presentations of analysis and business results to business unit leaders
- Develop analytics proof of concepts on emerging trends in different vertical areas to develop new analytical PoCs for Competency centre
- Evaluate and compare algorithm performance based on large, real-world data sets
- Work with product/business owners to map business requirements into products / productized solutions and/or working prototypes of ML algorithms
- Leverage data to analyze the business unit function, identify the business drivers and recommend strategy and future course of actions
- Conceptualize modeling framework, define data requirement, create predictive variables and co-ordinate model implementation with other business partners, and create experimental designs to understand drivers of business performance.

**Desired Skills and Experience**:

- Excellent communication skills, both verbal and written
- Strong analytical and problem-solving skills
- Expertise in developing business presentations