Look for 13+ years profiles only
Responsibilities
- Gathers, interprets, and manipulates structured and unstructured data to enable analytical solutions for the business.
- Selects the appropriate modeling technique and/or technology with consideration to data limitations, application, and business needs.
- Build various ML Models within the Model guidelines and framework.
- Consults with peers for guidance, as needed.
- Translates business requirements into specific analytical questions, build ML Models and present model outcomes to non-technical business colleagues.
- Consults with Data Engineering, IT, the business, and other internal stakeholders to deploy analytical solutions
- Stay current with emerging trends and technologies in data quality management, data profiling, data cleansing tools and AI/ML.
- Collaborate with data governance teams to ensure compliance with regulatory requirements and industry and legal standards related to data quality and privacy.
- Able to identify GenAI use cases given in various business scenarios and come up with possible solutions.
- Familiar with various GenAl technologies, Prompt Engineering, RAG etc
Skills & Qualifications
- 10 to 12 years of relevant experience, and 6+ years of experience in data science, machine learning, quantitative analytics (Mathematics, Statistics or Operational Research etc) roles
- Master’s degree in computer science, Statistics, or a related field (Mathematics, Operational Research, Data Science)
- Experience in Building and validating statistical, machine learning, and other advanced analytics models.
- Experience in Regression (multiple, Logistic etc), Classification (Decision Tree, Random Forest, XGBoost etc) and Time series Forecasting models (ARIMA), Segmentation, NLP, Deep Learning and Graph Analytics.
- Experience in Data Mining, Python, R, SQL, and familiarity with ML technologies
- Experience in using ML Libraries.
- Working Experience in Domino Data Lab, AWS Sagemaker, Snowflake are a plus
- Experience using business intelligence tools (e.g. Tableau) and data frameworks (e.g. Hadoop)
- Excellent problem-solving, analytical skills and attention to detail, with the ability to identify patterns, trends, and anomalies in data.
- Ability to write code that is easy to follow, well documented, and commented where necessary to explain logic (high code transparency).
- Experience in querying and preprocessing data from structured and/or unstructured databases using query languages such as SQL, HQL, NoSQL, etc.
- Experience in working with structured, semi-structured, and unstructured data files such as delimited numeric data files, JSON/XML files, and/or text documents, images, etc.
- Strong communication and collaboration skills, with the ability to effectively interact with technical and non-technical stakeholders.
From:
mary,
Yochana IT solutions
mary@yochana.com
Reply to: mary@yochana.com