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Data Scientist (ml/llm/gen Ai/agentic Ai) @ Crescendo Global

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Crescendo Global  Data Scientist (ml/llm/gen Ai/agentic Ai)

Job Description

Data Scientist (ML/GEN AI/AGENTIC AI/Time Series/Classic ML)

Exp - 4 to 8 Years

Location - Gurugram/Noida/Bangalore/Pune


Role & Responsibilities Overview:

  • Collaborate with business and data teams to define, design, and develop cutting edge AI/MLGen AI algorithms to solve real-world business problems
  • Analyze structured and unstructured data from a number of drivers in the interest of solving specific questions/problems with processes in the various functional areas
  • Communicate findings and results to non-technical stakeholders and provide actionable insights.
  • Optimize and fine-tune existing ML/AI models to improve their performance and accuracy.
  • Ensure data privacy and security practices are upheld throughout the AI development process.
  • Experience in using Python and hands on experience in building models with machine learning frameworks or algorithms
  • Develop/Support GenAI solutions for NLP involving LLM (Large Language Models) such as GPT, Flacon, and LLaMA among others, or for Computer Vision involving GANs, Diffusion models etc.
  • Track record in data modelling and data analytics tools like, SQL, Python and good knowledge in advanced analytics / Machine learning / NLP / statistical / data mining / Text mining techniques
  • Analyze structured and unstructured data from a number of drivers in the interest of solving specific questions/problems with processes in the various functional areas
  • Deliver industry best practices, and create code standards, presentations and other relevant documents basis stakeholder requirements.
  • Work in close collaboration with the Client team on establishing relationship with stakeholders, identify new opportunities, areas of growth
  • Provide Project, Client & Team Management and Monitor progress of deliverables on regular basis and ensure timely resolution of issues
  • Brainstorming on pain areas/Identifying reasons for issues/Issue Resolution, diagnosis of inefficiencies in the current process and figuring out ways to resolve it
  • Provide technical direction to project team members across data modeling, data manipulation, visualization, predictive modeling and reporting in projects across Insurance Value Chain
  • Facilitate client working sessions and lead recurring project status meetings

Candidate Profile:

  • Bachelors/Master's degree in economics, mathematics, computer science/engineering or related areas; candidates with BA/S degrees in the same fields from the top tier academic institutions are also welcome to apply; Professional certifications including (but not limited to) CFA/CA/FRM are preferred)
  • 4 to 8 years experience in data science preferably in any of these (ML/GEN AI/AGENTIC AI/Time Series/Classic ML)
  • Relevant experience in building large scale machine learning or deep learning models (LLM)
  • Experience in using Python and hands on experience in building models with deep learning frameworks like Tensorflow, PyTorch, Keras etc.
  • Good knowledge of integration technologies like APIs or cloud computing technologies like Snowflake will be a plus
  • Demonstrated capability in adhoc data analysis and solving abstract or vague problems
  • Strong track record of achievement, solid analytical ability, and an entrepreneurial hands-on approach to work
  • Outstanding written and verbal communication skills
  • Able to work in fast pace continuously evolving environment and ready to take up uphill challenges
  • Able to understand cross cultural differences and can work with clients across the globe

Job Classification

Industry: Analytics / KPO / Research
Functional Area / Department: Data Science & Analytics
Role Category: Data Science & Machine Learning
Role: Data Scientist
Employement Type: Full time

Contact Details:

Company: Crescendo Global
Location(s): Pune

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Keyskills:   Data Science Machine Learning Python Agentic Ai Generative Ai Natural Language Processing Time Series Deep Learning SQL

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