Description

You will develop and deploy machine learning models to solve complex business problems using structured and unstructured data.

Responsibilities

• Build and validate machine learning models, including regression, classification, time series forecasting, segmentation, NLP, deep learning, and graph analytics.
• Translate business requirements into specific analytical questions and present model outcomes to non-technical stakeholders.
• Identify GenAI use cases and design solutions using prompt engineering and RAG.
• Collaborate with Data Engineering, IT, and data governance teams to deploy solutions and ensure regulatory compliance.
• Manipulate and preprocess data from structured, semi-structured, and unstructured sources including SQL, NoSQL, JSON, and XML.

Required Skills

• 10 to 12 years of relevant experience, with 6+ years specifically in data science, machine learning, or quantitative analytics.
• Master’s degree in Computer Science, Statistics, Mathematics, Operational Research, or Data Science.
• Proficiency in Python, R, and SQL.
• Extensive experience with data mining and machine learning libraries.
• Expertise in statistical modeling, including Logistic Regression, Decision Trees, Random Forest, XGBoost, and ARIMA.
• Ability to write transparent, well-documented, and commented code.
• Experience querying and preprocessing data from various database types and file formats.
• Strong analytical skills to identify patterns, trends, and anomalies in complex datasets.

Preferred Skills

• Working experience with Domino Data Lab, AWS SageMaker, or Snowflake.
• Experience with Tableau, Hadoop, or other business intelligence and data frameworks.

Key Skills

Education

Bachelor's degree in Computer Science