Executive - Data Scientist

The purpose of this role is to works on new ways of capturing and analyzing data to be used by the analysts; research and devise innovative statistical models for data analysis. Along with developing models, using machine learning, or incorporating advanced programming to find and analyze data.

Responsibilities

• Work with stakeholders throughout the organization to identify opportunities for leveraging company data to drive business solutions.
• Use predictive modeling to increase and optimize customer experiences, revenue generation, ad targeting and other business outcomes.
• Participate in exciting projects covering the end-to-end Data Science lifecycle – from raw data cleaning and exploration with primary and third-party systems, through advanced state-of-the-art data visualization and Machine learning development.
• Strong expertise in developing explainable ML algorithms (e.g., regression, classification, clustering) and staying current with AI trends and advancements.
• End-to-end project ownership: From translating business needs into technical solutions, to building data/ML pipelines, deploying models, and implementing MLOps.
• Partner with stakeholders to ensure solutions meet requirements and translate technical values in business terminology.
• Skilled in building data stories from insights and using data mining techniques to generate insights.
• Review and validate models developed by team members and external party before production release.
• Develop company A/B testing framework and test model quality.
• Experience with cloud and big data architecture.
• Perform data exploration to find patterns in the data and understand the state and quality of the data available.
• Utilize Python code for analyzing data and building statistical models to solve specific business problems.
• Evaluate ML models and fine tune model parameters considering the business problem behind.
• Deploy ML models into production that work as standalone data services.
• Build customer-facing reporting tools to provide insights and metrics which track system performance.
• Stay up to date about developments in Data Science and relevant fields to ensure that outputs are always relevant.

Experience & Skills

• Experience in implemented machine learning algorithms and Deep learning algorithms
• Excellent in statistical modeling, predictive modelling and inferential statics
• Sound knowledge of Python’s ML stack
• Knowledge of statistics and experience using statistical packages for analyzing datasets (Excel, SPSS, SAS etc)