Candidates should have significant hands-on experience with analytical projects using AI/ML techniques.
Candidates will be expected to successfully prioritize and manage multiple analytical projects / ad-hoc requests
Hands-on experience in Predictive and Prescriptive Analytics
Good exposure to various techniques like linear/logistic regression models, discrete choice models, time-series models, dimensionality reduction, and unsupervised learning techniques
Good technical depth with strong analytical/programing skills and ability to apply technical knowledge to do research.
R / SAS / Python/SQL or other quantitative analysis programming skills
Should have strong hands-on experience in GitHub and GCP tools such as Big query, vertex AI, data proc, ETL in GCP, deployment and GenAI, artifact registry in GCP.
Responsibilities
Develop statistical methodologies and deploy analytical tools to support different business initiatives
Continual enhancement of statistical techniques and their applications in solving business objectives
Compile and analyze the results from modeling output and translate into actionable insights
Acquire and share deep knowledge of data utilized by the team and its business partners
Collaborate with various stake holders to create/improve data products to meet business objectives.
Support and share knowledge with other team members for cross functional collaboration.
Evaluate new tools and technologies to improve analytical processes
Set own priorities and timelines to accomplish projects (accountability for project deliverables)
Qualifications
Need 4 years Bachelor or Masters in mathematics/Statistics/Applied Mathematics/Applied Statistics.
2 to 3 years experience in AL/ML techniques and GCP tools with strong SQL, R and Python knowledge.
Good exposure to various techniques like linear/logistic regression models, discrete choice models, time-series models, dimensionality reduction, and unsupervised learning techniques.
