The Analytics and Insights team is seeking a data scientist who loves working on complex problems and getting things done. The ideal candidate combines excellent business acumen and communication skills with outstanding analytical skills. If you are detail-oriented, enjoy solving complex data challenges, and are passionate about data, we want to hear from you. As a Data Scientist, you will work with data analysts, managers and engineers to: resolve ambiguity with data, play a crucial role in the iteration and optimization of analytics and ML products and support data-driven decision-making on a key project for the organization. You'll be working directly with an experienced (and fun) team of brilliant people in a dynamic environment to grow the company that is revolutionizing the cloud computing world.
Responsibilities:
- The Candidate would be tasked with solving a real-life business problem that requires processing/analysing TBs of data and handling variety of data sources
- The candidate will be expected to deal with data extraction and munging, using appropriate ML techniques to build data science solutions and to implement these solutions in production.
- The work is organized as a project with clear deliverables and stringent timelines
- The Candidate would collaborate with other team members who would provide support and mentoring
- The Candidate would proactively investigate, report, and where possible, address data quality issues
Core Skills:
- Experience in using LLMs , both open source & proprietary models
- Experience in building Q&A models using RAG , fine tuning LLMs – beyond prompt engineering techniques.
- Experience in using tools like Langchain , LLamaIndex, vector databases is preferred
- Understanding of LLM Ops is a big plus
- Strong SQL skills (6-7 Years of hands-on experience with complex queries and data munging)
- Deep Machine Learning expertise (hands on with 6-7 years of experience)
- Strong expertise in Python (particularly Machine Learning Libraries)
- Experience implementing machine learning solutions in at least 3-5 real-life Analytics Projects (Excluding Academic/side projects)
- Solid fundamentals, knowledge of supervised, unsupervised, machine learning and deep learning algorithms, such as classifiers, cluster analysis, dimension reduction, regression, time series forecasting, boosting/bagging, model explain ability techniques
- Exposure to deep learning algorithms and areas such as NLP is a strong plus.
- Excellent communication (written/verbal), presentation and facilitation skills
- Ability to engage with business teams directly, especially with key stakeholders spread across different Geos (particularly AMER and EMEA)
- Great presentation skills