Executive - Data Scientist

We are seeking a highly motivated and analytical professional to join our team as an Executive - Data Scientist. To support data-driven decision-making by analyzing complex datasets, developing predictive models, and delivering actionable insights that contribute to the organization's strategic goals

Tasks & 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.
• Selecting and employing advanced statistical procedures to obtain actionable insights.
• Cross-validating models to ensure their generalizability.
• Work on regression and classification problems on tabular, textual and image data.
• Work on forecasting, anomaly detection and time-series analysis.
• Build recommendation engines.
• Develop company A/B testing framework and test model quality.
• Query large datasets in AWS Redshift to extract the necessary data that will feed ML models.
• 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.

Requirements:

• 4 years of hands-on experience in implementing machine learning algorithms such as Linear regression, Gradient boosted trees, Neural networks.
• Excellent in statistical modeling and math.
• Intermediate knowledge of Python’s ML stack: Pandas, Matplotlib, Sklearn, Tensorflow.
• Knowledge of statistics and experience using statistical packages for analyzing datasets (Excel, SPSS, SAS etc)
• Knowledge of programming languages like SQL, Oracle, R, MATLAB, and Python.
• Planning, organizing, and analytical skills.