Senior Associate, Data Science (Chambord)

About the job

GALE is the world’s first and only Business Agency. We bring business strategy to brand storytelling to drive enterprise value. With expertise in strategy, media, CRM, creative, performance marketing, and technology, GALE creates integrated marketing systems and campaigns that grow businesses in significant ways. Founded in 2014, the agency has since been named AdAge’s Business Transformation Agency of the Year and Adweek’s U.S. Media Agency of the Year and has been recognized for its innovative creative at the Cannes Lions.

We work with brands such as Delta, Uber, Starbucks, Chili’s, Hard Rock, MilkPEP, Diageo, Cotton, IHG and more. If you’re driven by a passion to build something great, a desire to innovate, and a commitment to achieve excellence in your craft, GALE is a great place for you!

Your Impact

We're currently seeking a Senior Associate, Data Science to join our rapidly growing data science and analytics team – one that has a passion for working with real world data to derive actionable insights. Successful candidates for the role will work with clients and internal stakeholders to define, prototype, and produce custom solutions using state-of-the-art big data platforms, analytics, and machine learning. The ideal candidate will have a background in a quantitative field and have experience with large datasets, Amazon Web Services ecosystem, statistical analysis, and client‑facing activities. They will be enthusiastic in solving business problems with a propensity to be results oriented. You will have the opportunity to work across varying sets of data with a variety of clients.

What you’ll do

• Work on research‑based initiatives using advanced machine learning methods focusing on tangible outcomes for our clients
• Implement machine learning models and data‑driven solutions to drive growth and decision making for our clients
• Prepare and integrate various types of data (structured/non‑structured) for modelling and analyses.
• Define, build, and present statistical and machine learning solutions for a wide range of industries
• Conduct various analyses, such as deriving business insights from market research surveys, customer segmentation, and social media analysis
• Build prototypes, proof of concepts, or APIs to showcase the models
• Research and learn new methods, tools and technologies presented in research communities to implement, experiment, and adapt within data science initiatives

Who You Are

• 3 – 5 years of experience with machine learning algorithms and their application
• At least 3 years of experience in data pipelining, preprocessing, modeling, and analysis
• Fluent in SQL and Python
• Strong grasp of statistics
• Experience with one or more of the following databases: PostgreSQL, AWS Redshift, Google BigQuery, Snowflake, SQL Server, and MySQL
• Strong influencing skills to ensure clients and internal stakeholders adopt the optimal data science and analytics solutions

Nice to Have

• Experience in consulting and/or advertising industry is preferred
• Experience with implementing machine learning solutions in a production environment
• Comfortable with presenting in front of clients and internal stakeholders
• Experience with interactive visualization of data in Shiny, D3, or Dash
• Familiarity with the AWS and GCP ecosystems
• Some familiarity with media measurement techniques

Compensation

To comply with equal pay and salary transparency laws in various locations, we believe the target compensation for this role is $115,000 to $130,000 per year. Actual compensation is influenced by a wide array of factors including but not limited to skill set, qualifications, job performance, level of experience, location, and business needs. For more information on other benefits we offer, please visit our careers page.

Hybrid Work Requirement

Note: Hybrid work in office is an essential function of the job.

Equal Opportunity Employment

GALE is an equal opportunity employer. All applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran, or disability status.