Virtusa to Adopt Google Workspace with Gemini in Expansive New Partnership | Read more
Secondary: Data Analysis and Processing, Data Visualization
Exploratory Data Analysis (EDA): Conduct thorough exploratory data analysis to uncover insights and trends from raw datasets.
SQL: Proficiency in SQL to extract, manipulate, and analyze large datasets from relational databases.
AI/ML Models: Strong experience in designing, building, and deploying AI or Gen AI based solutions.
Cloud Technology : Must have a strong exposure in deploying AI/ Gen AI Models in Cloud
Machine Learning: In-depth understanding and practical experience with machine learning algorithms and techniques.
Deep Learning: Hands-on experience in deep learning models, particularly in NLP and computer vision.
Natural Language Understanding (NLU): Expertise in applying NLU techniques to process and understand human language data.
Python: Strong programming skills in Python, especially for data science tasks and NLP.
Hugging Face Transformers: Experience with Hugging Face Transformers library for implementing state-of-the-art NLP models.
BERT: Expertise in utilizing BERT for a variety of NLP tasks including text classification, named entity recognition, and question answering.
NLP Algorithms: Knowledge of advanced NLP algorithms and techniques for text analysis and understanding.
Model Fine-Tuning: Ability to fine-tune pre-trained models to improve their performance on domain-specific tasks.
Text Analytics: Experience in text mining and extracting useful insights from large text datasets.
Machine Learning Frameworks: Proficiency with machine learning frameworks like TensorFlow and PyTorch.
Data Analysis and Processing: Strong skills in data analysis and preprocessing and feature engineering for model readiness.
Data Visualization: Ability to present complex data and insights using visualization tools like Matplotlib, Seaborn, or similar.
State-of-the-Art NLP Models: Integrate and apply cutting-edge NLP models and algorithms to extract valuable insights from large text datasets.
Cross-functional Collaboration: Work closely with cross-functional teams to understand business needs and translate them into technical solutions using NLP techniques.
Reporting and Presentation: Present findings and insights to stakeholders through clear, concise, and compelling reports and presentations.
Qualifications:
Minimum 5+ years of experience in Data Science, particularly with Gen AI, NLP, ML, and Deep Learning techniques.
Strong analytical and problem-solving skills.
Ability to communicate complex technical concepts to non-technical stakeholders.
Excellent teamwork and collaboration skills in a dynamic environment.
Primary : Python, SQL, Gen AI, NLP, ML, and Deep Learning techniques
Secondary: Data Analysis and Processing, Data Visualization
Exploratory Data Analysis (EDA): Conduct thorough exploratory data analysis to uncover insights and trends from raw datasets.
SQL: Proficiency in SQL to extract, manipulate, and analyze large datasets from relational databases.
AI/ML Models: Strong experience in designing, building, and deploying AI or Gen AI based solutions.
Cloud Technology : Must have a strong exposure in deploying AI/ Gen AI Models in Cloud
Machine Learning: In-depth understanding and practical experience with machine learning algorithms and techniques.
Deep Learning: Hands-on experience in deep learning models, particularly in NLP and computer vision.
Natural Language Understanding (NLU): Expertise in applying NLU techniques to process and understand human language data.
Python: Strong programming skills in Python, especially for data science tasks and NLP.
Hugging Face Transformers: Experience with Hugging Face Transformers library for implementing state-of-the-art NLP models.
BERT: Expertise in utilizing BERT for a variety of NLP tasks including text classification, named entity recognition, and question answering.
NLP Algorithms: Knowledge of advanced NLP algorithms and techniques for text analysis and understanding.
Model Fine-Tuning: Ability to fine-tune pre-trained models to improve their performance on domain-specific tasks.
Text Analytics: Experience in text mining and extracting useful insights from large text datasets.
Machine Learning Frameworks: Proficiency with machine learning frameworks like TensorFlow and PyTorch.
Data Analysis and Processing: Strong skills in data analysis and preprocessing and feature engineering for model readiness.
Data Visualization: Ability to present complex data and insights using visualization tools like Matplotlib, Seaborn, or similar.
State-of-the-Art NLP Models: Integrate and apply cutting-edge NLP models and algorithms to extract valuable insights from large text datasets.
Cross-functional Collaboration: Work closely with cross-functional teams to understand business needs and translate them into technical solutions using NLP techniques.
Reporting and Presentation: Present findings and insights to stakeholders through clear, concise, and compelling reports and presentations.
Qualifications:
Minimum 5+ years of experience in Data Science, particularly with Gen AI, NLP, ML, and Deep Learning techniques.
Strong analytical and problem-solving skills.
Ability to communicate complex technical concepts to non-technical stakeholders.
Excellent teamwork and collaboration skills in a dynamic environment.
Key job details
About Virtusa
Teamwork, quality of life, professional and personal development: values that Virtusa is proud to embody. When you join us, you join a team of 27,000 people globally that cares about your growth — one that seeks to provide you with exciting projects, opportunities and work with state of the art technologies throughout your career with us.
Great minds, great potential: it all comes together at Virtusa. We value collaboration and the team environment of our company, and seek to provide great minds with a dynamic place to nurture new ideas and foster excellence.
Virtusa is an Equal Opportunity Employer. All applicants will receive fair and impartial treatment without regard to race, color, religion, sex, national origin, ancestry, age, legally protected physical or mental disability, protected veteran status, status in the U.S. uniformed services, sexual orientation, gender identity or expression, marital status, genetic information or on any other basis which is protected under applicable federal, state or local law.
Applicants may be required to attend interviews in person or by video conference. In addition, candidates may be required to present their current state or government-issued ID during each interview. All candidates must be authorized to work in the USA.
Learn more
Awards and recognition
Syncing your Virtusa Information
Syncing Complete
Exporting your personal Virtusa brand items
Export Complete
Check your downloads folder for files and implementation instructions.
Assets are now available in your profile for future editing and use.
Loading your existing headshots
Please select any one of the images below
Downloading Secure Assets
Signing out