Title: Senior Data Scientist
Location: Charlotte, NC (onsite)
Duration: 6 to 12 months
Position type: W2 contract.
We are Looking for a hands-on Senior Data Scientist to undertake multiple advanced analytics initiatives like Forecasting, Predictions etc. that will enable us deliver Operational Excellence and provide actionable insights to business users.
The Role
Responsibilities:
The Data Scientist is responsible for executing the full scope of advanced analytic techniques with the objectives of creating quantitative and qualitative models, data mining, causal inferences, predictions, optimizations, and recommendations.
This position is for a self-starter with leadership qualities, responsible for formulating and managing projects, as well as developing data science models, and working with key business, data and technology leaders to establish roadmaps and deliver high value analytic projects.
Position requires strong command of various data mining and advanced analytical techniques to produce easy to use analytical solutions.
Contributes to the strategic vision and integrates a broad range of ideas regarding setting the strategy around gathering, organizing, and extracting qualitative and quantitative relationships and trends from large amounts of data.
Recognized across the organization for organizing and developing data warehouses for optimal decision support. Leads the design, development and implementation of complex data management, storage applications, often using new technologies.
Exercises judgment within broadly defined practices and policies in selecting methods, techniques, and evaluation criterion for obtaining results. Work leadership may be provided by assigning work and resolving problems.
Requirements:
Strong knowledge of Machine Learning Algorithms and techniques
Strong knowledge of Generative AI (keywords- zero shot, few-shot, RAG, Fine-tuned (fine tuning) model, etc.)
Expert with NLP and must have worked on a few large-scale projects
Strong knowledge of Data Science
Must know Statistical techniques/tests.
Super comfortable with Python, Spark, SQL
Hands-on experience on either AWS/GCP/Azure
Good knowledge of Deep Learning and Transformers architecture.
Experience with building Deep learning models.
Experience with MLOps principles and MDLC lifecycle.
Experience with deploying Deep learning models.
Must be hands-on using Spark, Kubernetes, Docker, etc.
Good to have- Hands-on experience on either AWS/GCP/Azure