Data Scientist

Position Details

What You Will Do :

• Defining Problem Stements - Work closely with cross-functional teams, including analysts, product managers and domain experts to understand business requirements, formulate problem statements, and deliver relevant data science solutions.
• Machine Learning Model Development - Develop and optimize machine learning models by processing, analyzing and extracting data from varying internal and external data sources.
• Data Preprocessing Own and manage complex ETL pipelines to clean, preprocess and transform large datasets.
• Feature Engineering - Identify and engineer relevant features to enhance model performance and accuracy
• Model Deployment and Evaluation Design and implement robust evaluation metrics and frameworks to assess and monitor the performance of machine learning models

Operational Management

• Develop algorithms and predictive models to solve critical business problems.
• Develop tools and libraries that will help analytics team members more efficiently interface with large amounts of data.
• Analyze large, noisy datasets and identify meaningful patterns that provide actionable results.
• Understand and recommend the best technology and / or tools to execute a data science / machine learning task in development and production.
• Create informative visualizations that intuitively display large amounts of data and / or complex relationships.
• Provide and apply quality assurance best practices for data science services across the organization.
• Develop, implement, and maintain version control and testing processes for modifications to algorithms and data analytics.

Who You Are :

• A Master’s degree in Mathematics, Statistics, Data Analytics, Computer Science or directly related field.
• Preference will be given to candidates with PhD in the field of Science / Mathematics / Statistics and relevant experience in machine learning algorithms, tools and technology.
• Extensive experience solving analytical problems using quantitative approaches, preferably in the insurance sector.
• Comfortable in manipulating and analyzing complex, high-volume, high-dimensionality data from varying sources using Python / R libraries and SQL
• Familiarity with relational, SQL and NoSQL databases.
• Knowledge of statistical analysis tools such as R, is a plus.
• Expert knowledge of scripting in Python using OOPS concepts
• Experience with PowerBI.
• Experience in using cloud AutoML tools including on Azure, Amazon, Google, etc
• Experience with cloud platforms (e.g., AWS, Azure, Google Cloud) and big data technologies.
• Experience in DevOps or MLOps is a plus
• Experience with DS or ML frameworks and libraries (e.g., Spark, TensorFlow, PyTorch) is a plus.
• Experience in owning and managing complex ETL pipelines using Control M, AirFlow is a plus.
• A strong passion for empirical research and for answering hard questions with data.
• A strong hunger to learn and use new and latest technologies and tools.
• Experience working in a team-oriented, collaborative environment.
• A flexible analytic approach that allows for results at varying levels of precision.
• Ability to communicate complex quantitative analysis in a clear, precise, and actionable manner.
• Good written and verbal communication skills.
• Strong technical documentation skills.
• Good interpersonal skills.
• Keen attention to detail.
• Ability to effectively prioritize and execute tasks without supervision in a high-pressure environment.
30+ days ago