Data Scientist Offline

WHO WE ARE

At Bennett Data Science, we’ve been pioneering the use of predictive analytics and data science for over ten years, working with the biggest brands and retailers around the world. We’re at the top of our field because we focus on making our clients’ products better. Our deep experience and product-first attitude set us apart from other groups and get us the business results our clients want.

WHY YOU SHOULD WORK WITH US

You’ll be exposed to a wide range of clients who are at the cutting edge of innovation in their field and get to work on fascinating problems, supporting real products, with real data. We help lots of companies, from some of the largest companies in the world to small startups in Silicon Valley who are building the next big thing. Your perks include expert mentorship from senior staff, competitive compensation, a flexible work schedule, and the ability to work from anywhere in the world.

Data Scientist - General Requirements:

Data scientists at BDS utilize their analytical, statistical, and programming skills to collect, analyze, and interpret large data sets. They use this information to develop data-driven solutions to difficult business challenges for our clients. Our data scientists commonly have a university degree in statistics, math, data science, computer science, or economics and are required to have a wide range of technical competencies including:

- Descriptive statistics

- Machine learning

- Python / Jupyter programming/scripting

- SQL queries

- Model building and deployment

- Initial data analysis, data cleaning/wrangling, and exploratory data analysis

- Data visualization and communication

As a distributed team, we value self-starters with a strong work ethic who communicate well across online channels.

Responsibilities for Data Scientists:

- Work with project owners and stakeholders to interpret client objectives and offer data-backed solutions

- Mine and analyze data from large databases or flat files

- Assess the effectiveness and accuracy of new data sources to address client objectives

- Develop custom machine learning models across multiple applications

- Coordinate with stakeholders to implement models and monitor outcomes

- Develop processes and tools to monitor and analyze model performance, accuracy, and drift

- Understand and interpret A/B testing results related to deployed models

- Must be able to build and deploy predictive models with little or no supervision

Data Scientist - Specific Requirements

A successful data scientist has 2 or more years of experience, is confident in building predictive models, uses appropriate statistical techniques to describe data distributions or communicate findings, is a proven self-starter, and exhibits the following skills:

- Regularly creates, deploys, and uses machine learning algorithms to solve business objectives

- Experience using natural language processing (NLP) methods

- Familiar with translating business objectives into (predictive) models

- Familiar with objective function minimization and product-driven model development

- 3+ years of coding experience in Python with strong capabilities in major frameworks such as Pandas, sklearn

- Experience building data science pipelines to ingest, transform, and extract value from data

- Strong capability in describing data distributions using statistical methods

- Strong knowledge of SQL

- Accomplished at combining data from multiple sources by grouping/aggregation to produce desired datasets

- Expert at visualizing/presenting data for stakeholders

- Strong communication skills especially describing technical work during weekly progress meetings