Senior Data Analytics Engineer

Role Purpose:

As a Data Analytics Engineer in Global Solutions, this role requires collaboration with different lines of business, building capabilities to better harness the power of data using Machine Learning and Artificial Intelligence capabilities. This role uncovers enterprise insights and drive business results using smarter data analytics and implement enterprise data products and data management applications that improve operational effectiveness and provide actionable data analytics and insights.

Role Details – Key Responsibilities and Accountabilities:

Requirements:

• Experienced in Engineering/Technology with knowledge on Data Engineering, Data Analytics and Advanced Analytics and its application.


• Master is Artificial Intelligence, Business Analytics, Machine Learning preferred.


• Drive actionable insights from business data, by leveraging analytics and data science tools and techniques.


• Develop PoC, present to the business and evolve the solution. Take forward the solutions into Pipelines/APIs as needed by the business.


• Experienced in End-to-End Machine Learning workflow which includes activities like Data Collection, Feature Engineering and Data transformation, Model training and deploying models in production.


• Proficiency with Python/PySpark/SQL , visualization tools like Power BI/Tableau , cloud friendliness (GCP/Azure etc) to leverage distributed computing/scalability ,understanding of Data Warehousing and data Lake concepts


• Operationalize and monitor machine learning models using MLflow/Kubeflow , Design & implementation of DevOps principles in Machine Learning


• Responsible for delivering Executive dashboards end to end with actionable insights to enable decision making.

Definition of Success

The Successful Applicant:

• Bachelor’s degree in mathematics, Computer Science or similar engineering discipline


• Masters in a quantitative field such as Research, Computer Science, Engineering, Applied Math, Economics, Statistics, Analytics, Artificial Intelligenc,e Machine Learning, Management/Business Information Systems (or related degree).


• Minimum 8 years of experience, in data science settings with a focus on developing projects using Data warehousing and cloud, with experience in Shared Service functions – Finance, HC, Procurement mandatory.

To be successful in thisrole, your background must include the following:

• Experience in designing and implementing User Interfaces at an Enterprise Level.


• Strong system architecture and design experience to include deploying enterprise applications in cloud environments.


• Experience with scripting and programming languages in Python, R and Java.


• Experience in Design Thinking, commercial interests, and technological constraints


• Experience conducting qualitative and quantitative research and synthesizing to provide insights, identify opportunities, and generate conceptual frameworks.

Functional/Technical Competencies

Skills sets includes:

• Data Analytics skills to Visualize the data (Power BI, Tableau ,React.js )


• Data Engineering and backend creation using SQL, Python, Pyspark ,Data warehousing , Cloud (Azure/AWS) ,creating ETL pipelines , Airflow


• Data Science :ML/DL libraries using Sklearn, tensorflow, Keras , NLP, RNN ,CNN


• Deployment and operationalization of developed application using concepts of DevOps (Containers, Docker, Git, Jenkins, MLFlow )

Personal Characteristics and Required Background:

• Critical Thinking, Decision Making abilities


• String Communication Skills and ability to convey and convince effectively


• Good knowledge and understanding of technologies