We’re looking for someone with a deep interest in data and analytics and the dedication to apply that passion. We need someone that possesses the technical ability to write modular, packaged code and implement data science methods for a diverse set of applications, as well as uncover insights from the models and communicate them concisely and clearly to stakeholders at varying levels of technical sophistication. The role also requires an observant attention to detail, the ability to work well on a small team, and a self-starter approach to problem-solving and upskilling.
As a Data Scientist, you will:
- Work closely with team members on design and execution of experimentation efforts, contributing to internal analytics libraries and integrating statistical theory
- Collaborate on prototyping new data science methodologies, including Synthetic Data, by translating needs identified with stakeholders into analytic frameworks that can be built into scalable user-facing tools
- Build, maintain, and enhance existing codebases
- Synthesize academic research, tech innovations, and cloud scalability, into R&D that elevates business value for clients, both current and prospective
- Validate AI and other analytics innovations from marketing science and data science teams globally
- Provide consulting and validation for internal teams and clients on areas ranging from statistical principles to sampling theory and data hygiene to LLM implementation
Requirements:
- High proficiency writing Python and/or R, including the ability to produce and maintain reusable and modular codebases (beyond scripting and notebooks)
- Bachelor’s degree in Statistics, Math, Data Science or related
- Desire to work in a highly collaborative, fun, consensus-oriented environment.
- Experience in analytics, extracting and surfacing value from quantitative data
- Familiarity with LLM internals, prompting, agentic frameworks, as well as other generative AI models (e.g. tabular diffusion, GANs, VAEs)
- Ability to lucidly communicate data science concepts verbally and in written form
Pluses:
- Experience with Synthetic Data (i.e. Data Boosting/Augmentation, Digital Twins, Persona Bots, AI Respondents/Panels).
- Professional or academic experience with modern techniques and algorithms in machine learning and statistical computing such as generative models, neural networks, genetic algorithms, Bayesian modeling, data fusion, drivers analysis, clustering, predictive analytics, network analysis, Monte Carlo.
- Experience developing data science models in cloud platforms (e.g. GCP, AWS)
- Working knowledge of SQL and experience with database design and administration.
- Experience with collaboration tools (e.g. Atlassian suite) and version control systems (e.g. Git).
- Advanced degree (M.S., Ph.D.) but not required.
- Experience in the field of Market Research.
If you don’t meet 100% of the requirements, we encourage all who feel they might be a fit for the opportunity to apply. We may consider a variety of backgrounds for a particular role and are also committed to considering candidates for available positions throughout our organization, not just the one you’re applying to!
In accordance with NY/CO/CA/WA law, the estimated base salary range for this role is $80,000 to $85,000. Your final base salary will be determined based on several non-discriminatory factors which may include but are not limited to location, work experience, skills, knowledge, education and/or certifications.
What’s in it for you:
At Ipsos you’ll experience opportunities for Career Development, an exceptional benefits package (including generous PTO, healthcare plans, wellness benefits), a flexible workplace policy, and a strong collaborative culture.
To find out more about all the great reasons to work at Ipsos, how we’re making an impact around the world, and more about our benefits and employee programs, please visit:
Why Work at Ipsos | US
Commitment to Diversity
Ipsos recognizes the necessity of building an inclusive culture that values each employee’s individuality and diverse perspectives. For more than 40 years, our mission has been to generate and analyze data about society, markets, brands, and behaviors to provide our clients with the insights that elevate their understanding of the world. This could not be fulfilled without Ipsos’ diverse employees who compile and analyze this data—they are the essence of who we are and what we do.
We are committed to providing equal opportunity to all employees, creating an environment that promotes inclusion, and enabling employees from all walks of life to flourish. Ipsos encourages our employees to act in a respectful and responsible manner, in line with code of best practices concerning diversity and inclusion, human rights, equality, and civility for every individual.
Ipsos is An Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to age, race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, or any other protected class and will not be discriminated against on the basis of disability.
#LI-FM #LI Hybrid Onsite
About UsIpsos is one of the world’s largest research companies and currently the only one primarily managed by researchers, ranking as a #1 full-service research organization for four consecutive years. With over 75 different data-driven solutions, and presence in 90 markets, Ipsos brings together research, implementation, methodological, and subject-matter experts from around the world, combining thematic and technical experts to deliver top-quality research and insights. Simply speaking, we help the biggest companies solve some of their biggest problems, serving more than 5000 clients across the globe by providing research, data, and insights on their target markets. And we are proud of our continuous efforts in making Ipsos the best place to work! About the Team
The Ipsos Behavior Science Center consists of talent with both academic as well as market research industry experience who work across all of Ipsos, as well as with Ipsos clients, to develop and apply behavioral science to understand how consumers actually behave (as opposed to stated behavior).
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