Job details

Country

USA

State / Region / Province

North Carolina

Work Location

Charlotte, NC

Domain

Consulting

Interest Group

Infosys Limited

Skills

Technology|Data Science|Machine Learning

Company

ITL USA

Requisition ID

121300BR

Job description

Infosys is seeking a Data Science Lead with strong background in designing and building machine learning models / algorithms to implement predictive & prescriptive analytical solutions in areas such as customer loyalty, personalization and recommendations, customer segmentation and profiling, Sales Calls, E-mail and Direct mail targeting, retention analysis, churn assessment etc. The ideal candidate will be able to look at data from multiple sources and integrate data/inputs in a manner to build cause effect linkages to arrive at key issues. Ideally the candidate uses understanding of the problem to arrive at multiple solution alternatives keeping in mind the various stakeholders and assess the pros and cons of all the alternatives to arrive at the optimal solution.

Required Qualifications:

• Bachelor’s degree or foreign equivalent required from an accredited institution. Will also consider three years of progressive experience in the specialty in lieu of every year of education.
• At least 7 years of experience in Information Technology.
• Candidate must live within commuting distance of Charlotte, NC or be willing to relocate. Travel within the US may be required.
• U.S. citizens and those authorized to work in the U.S. are encouraged to apply.
• Strong knowledge of AI and ML algorithms and hands-on experience in using tools like Azure ML or AWS SageMaker to implement and deploy the models
• Hands on experience in SQL and Tableau
• Strong Statistical Modelling, Regression models (linear, lasso, ridge, and non-linear regression etc.) Time series modelling (ARIMA, fbprophet, ETS, etc.) and Machine learning
• Proven and proficient in Object oriented programming in Python.
• Collaborate with business users to assess and elaborate Analytics Uses cases
• Perform Data Wrangling to prepare data for analysis
• Perform Exploratory Data Analysis on customer data
• Develop, Test, Deploy and Monitor ML Models
• Work with other data scientists as a team to understand algorithms suggested and provide QA in algorithm choice from a business perspective

Preferred Qualifications:

• Hands on experience in SAS/Python
• Strong experience in Python data wrangling/analysis using Pandas, Numpy, Matplotlib, seaborn etc.
• Good understanding of version control tools like git & Experience building CI/ CD pipelines.
• Familiarity with deep learning libraries like Tensorflow, Keras, pytorch
• Understanding and awareness for Data science lifecycle
• Excellent business communication and excellent relationship management ability and the ability to work across business units within complex organization

The job may entail extensive travel. The job may also entail sitting as well as working at a computer for extended periods of time. Candidates should be able to effectively communicate by telephone, email, and face to face.

About Us
Infosys is a global leader in next-generation digital services and consulting. We enable clients in more than 50 countries to navigate their digital transformation. With over four decades of experience in managing the systems and workings of global enterprises, we expertly steer our clients through their digital journey. We do it by enabling the enterprise with an AI-powered core that helps prioritize the execution of change. We also empower the business with agile digital at scale to deliver unprecedented levels of performance and customer delight. Our always-on learning agenda drives their continuous improvement through building and transferring digital skills, expertise, and ideas from our innovation ecosystem.

Infosys provides equal employment opportunities to applicants and employees without regard to race; color; sex; gender identity; sexual orientation; religious practices and observances; national origin; pregnancy, childbirth, or related medical conditions; status as a protected veteran or spouse/family member of a protected veteran; or disability.