Sr. Data Scientist

Key Skills

Cloud computing, Data science techniques, Data Visualization, Google BigQuery, Google-Analytics, Machine learning techniques, matplotlib, NumPy, Pandas, plotly, Project management, Python Programming, SQL, TensorFlow

Job Description

Forbes believes in the power of entrepreneurial capitalism and uses it on various platforms to ignite the conversations that drive systemic change in business, culture and society. We celebrate success and are committed to using our megaphone to drive diversity, equity and inclusion.

As a Sr. Data Scientist at Forbes on the Business Intelligence team, you’ll have the opportunity to work on a variety of unique and interesting challenges. You'll be part of a highly effective team, who are leveraging data science to advance our business and drive revenue growth.

Responsibilities:

• Own the development of new and existing machine learning models with a focus on increasing revenue and helping the site understand it’s users

• Research and develop solutions to varied and complex business problems that touch all areas of data science (regression, classification, forecasting, nlp, clustering, etc.)

• Some current areas of focus include lookalike modeling, propensity, audience segmentation and churn

• Perform data mining on large structured and unstructured datasets to uncover insights

• Continuously improve your skills and knowledge through classes and independent research

What You Bring:

• 2-3 years of experience as a data scientist (plus if it’s in the publishing/media industry)

• MS in computer science, applied mathematics, statistics or other quantitative/computational discipline

• Experience applying data science in a business environment to create impact.

• 2-3 years of experience with Python & SQL

• 2-3 years relevant work experience with popular machine learning open-source libraries (pandas, numpy, sklearn, XGBoost, Tensorflow/Keras, etc.), cloud computing (Google Cloud Platform preferred), databases (BigQuery preferred), Web Analytics (Google Analytics 360 preferred)

• Solid understanding of traditional machine learning techniques, feature engineering and data cleansing/analysis

• Real-world experience with natural language processing, regression, classification, clustering and time series forecasting. Familiarity with deep learning approaches a plus

• Demonstrated problem solving skills and ability to present complex problems clearly

• Experience presenting findings to internal stakeholders at different levels

• Knowledge of data visualization tools (i.e.matplotlib, plotly)