Data Scientist

Responsibilities

• Work with Business stakeholders to understand Business requirements and desired business outcomes

• Perform exploratory data analysis on enterprise structured and unstructured data and explore data for training and building models

• Build and deploy machine learning inference models, monitor performance for models in production, remediate model drift

• Analyze results from models, perform Predictive and Prescriptive Analytics, generate insights and explain results to end users

• Integrate inference models with applications such as MS Dynamics

• Collaborate with team members to deliver innovative technologies, insights to Visa business units to save costs, facilitate data driven Business decisions, improve operations and efficiency gains.

• Research emerging trends and published papers in AI and Machine learning and apply learnings to solve Business problems

Qualifications

Basic Qualifications:

• 2 - 6 years of work experience with a Bachelor’s Degree or an Advanced Degree (e.g. Masters, MBA, JD, MD, or PhD)

Preferred Qualifications :

• 3 or more years of work experience with a Bachelor’s Degree or more than 2 years of work experience with an Advanced Degree (e.g. Masters, MBA, JD, MD)

• Master’s degree in Statistics, Operations Research, Applied Mathematics, Economics, Data Science, Business Analytics, Computer Science, or a related technical field preferred

• 4+ years’ experience in data-based decision-making or quantitative analysis

• Extracting and aggregating data from large data sets using SQL/Hive or Spark

• Analyzing large data sets using programming languages such as Python, R, SQL and/or Spark

• Generating and visualizing data-based insights in software such as Tableau or Power BI

• Proficiency in data analytics, data mining, machine learning, and related fields.

• Knowledge of Text mining, Natural Language Processing, Pattern recognition, Deep Learning, Graph algorithms required

• Proficiency in Python, Jupiter notebooks required

• Proficiency in IBM Watson APIs and Opensource ML/AI frameworks like Tensorflow, Pytorch etc nice to have

• Experience in building inference model APIs and scaling APIs preferred

• Knowledge of Hadoop and components like Hive, Oozie, Sqoop, Airflow, Nifi, Spark

• Knowledge of Kafka, Airflow, Apache Flint, Spark Streaming, Microservices, Building data products nice to have

• Knowledge of Data engineering (ETL and ELT) and Data warehousing concepts nice to have

• Knowledge of relational and NoSQL, Graph database concepts, systems architecture, and data structures

• Proficiency in Linux, Windows, Databases (Oracle, Sql server), SQL, Graph database(Neo4j)

• Excellent communication skills

Program/Project Overview

Based on the MVP scope we pulled together our integrated marketing, sales, and CS agile teams estimates to deliver on:

Visa Sales CRM Foundation: Enhance current version to industry standards including: Enabling Profiles, stand account data, activate territory alignment

Seamless Integration: Governance and connecting end to end flows: marketing to sales; sales to cs. Ensuring alignment on tools and customer journeys

Process and sales motions – Implementing new capabilities to seller journey lead sequencing, cpq , deal flow. and reporting

Iteration/ enhancement- working to the maintenance and future versions- North Star- Gen AI.