Data Science Intern – Pey/Co-Op

What You’ll Do

• Collect, analyze and visualize colossal datasets using a variety of emerging technologies to help solidify our understanding of users and improve product decision-making
• Assist in design, build and maintain an expanding set of robust predictive models and applications to drive forecast accuracy
• Contribute towards data science initiatives to recommend actionable business insights using big data analytics and machine learning techniques
• Leverage distributed and open-source computing tools for recommendations, classification, regression, and feature extraction, from logistic regression to matrix factorization, to deep learning neural networks
• Prepare detailed documentation to specify data sources, models and algorithms used and developed
• Collaborate with the engineering team to deploy models and algorithms in production
• Effectively communicate data insights in a non-technical manner to key stakeholders and senior management team

What You’ll Need

• Currently completing Bachelors or Masters degree in relevant disciplines (Mathematics, Computer Science, Statistics or other quantitative related discipline)
• Some experience in data mining, machine learning and statistical modeling
• Solid knowledge in regression, time series analysis, tree methods, neural network, sampling
• Proven track record of building and demonstrating business value from predictive models and data products
• Highly proficient in building statistical and algorithmic models with complex and large data sets such as supervised statistical learning, times-series analysis, regression analysis, data visualization and deep learning
• Capability to architect highly scalable distributed systems, using different open source tools
• Coding experience in SQL or Python or R
• Experience with AWS Kinesis, DynamoDB, Lambda, Redshift, Glue, Athena and Airflow
• An entrepreneurial mindset, likes working in an agile environment, driven to ship frequently
• Excellent communication and interpersonal skills
• Team-oriented, pragmatic, self-starting
• Likes to learn and grow with teammates in a highly collaborative and open environment
• Understanding of, or interest in, finance and investments

What We Offer

• Opportunity to work on a real product with very demanding paying enterprise clients
• Learning and self-development opportunities through online courses and knowledge sharing lecture sessions.
• Extended health coverage (Dental, Vision, Drug plan and other medical services)
• Life Insurance and AD&D coverage
• Paid vacation days, sick days, personal/ emergency days and extended long weekends.
• Monthly team lunches and social events (hosted virtually in light of Covid restrictions)