> Markdown version of [/jobs/ext/2709501-associate-data-science](https://www.wearedevelopers.com/jobs/ext/2709501-associate-data-science). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Associate, Data Science - **Company:** Horizon Media, Inc. - **Location:** New York, NY, United States - **Experience:** Expert - **Salary:** $100,000.0 - $120,000.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Microsoft Basic Data Partition, Big Data, Data Validation, Data Dictionary, Data Files, Data Transformation, Data Mining, Data Visualization, Relational Databases, Factor Analysis, Python (Programming Language), Machine Learning, Sentiment Analysis, Computational Statistics, Technical Data Management Systems, Unstructured Data, Information Technology, Data Analytics - **Published:** September 4, 2026 - **Apply:** https://www.careerjet.com/job/usc252ad890ee2fd25c62839b76cfc4b31/eaa ## About the Role * BS/BA degree in Computer Science, Statistics, Applied Mathematics, or a related field required. * 0-2 years relevant experience, preferably in a media, marketing or digital advertising environment. * Working knowledge of Big and basic data mining routines a must. * Expert knowledge in an analytic and programming language such as Python, R, or a similar language * Working knowledge of Predictive and Machine Learning a plus. * Persistence: Demonstrate tenacity and willingness to go the distance to get new things done. * Ability to work in a fast paced, multiple project environment on an independent basis and with minimal supervision. * A team player who can work collaboratively within the group and across business units/functions. * Strong verbal communication skills, extremely well-organized. * Business acumen - understands the strategic levers of the business and how analytics is a catalyst for decision making. ## Description The Associate, Marketing Science's main responsibility is to use advanced statistics and data science techniques to build qualified audiences for our client's campaigns. This person will apply sophisticated data science, modeling, and other advanced analytics techniques to help guide our clients' audience strategy to make their media campaigns resonate better and be more effective. Using data, ML, and the blu. Platform, the blu Marketing Sciences group brings to life the most qualified audiences for our clients addressable campaigns. These results and deliverables are a contributor and often "proof of concept" to Product enhancement and future capabilities. In addition to the technical aspects required, it will involve cultivating and maintaining effective working relationships with a variety of Agency groups. They must be intellectually curious with the drive and experience to identify, frame and solve business problems. They must be a critical thinker who can provide creative strategic solutions and who can follow-through with flawless execution. Highly driven with an exceptional work ethic, determination to overcome complex challenges, and a desire to have huge impact on the business. Responsibilities 30% Solutions Design & Innovation * Ability to understand and leverage blu. structured and unstructured data * Ability to build end-to-end data science solutions for a non-data science audience * Ability to generate clear, concise and comprehensive analyses that tell the story behind the data! * Data transformation/mining and generation of insights to explain audience performance and inform optimization * Data join process between blu audiences, media exposure and conversion events to build feedback loops * Analysis of audience conversion to KPIs * Increasingly utilize AI solutions to inform and expedite some or all of the required analysis 60% Technical & Analytical Excellence Audience Development * Machine Learning, Data Mining with Machine Learning with large datasets of Structured and Unstructured data. Data Validation, Predictive modeling, data visualization techniques. * NLP for sentiment analysis * Mathematical and Statistical libraries in Python and/or R * Experience in importing/exporting data for relational databases Measurement * Time series * Bayesian analysis * Causal Inference * Familiarity with relational databases * Solid understanding of data technology integrations across data sources and ecosystems, and ability to troubleshoot. * Knowledge of the data dictionaries and taxonomies of structured data sets * Cluster & Factor analysis * Ability to perform advanced data visualization 10% Product Innovation & Management * Become a power user to drive continuing improvement in the analysis and results supported by AI and the custom solutions built on top and around those * Experience working with and/or managing teams in product development * Consider design principles that scale and can be repeatable and/or extensible to other clients or industries * Participate in Product release management processes, including all levels of testing (Alph, Beta, QA, UAT) * Propose features, models, queries and requests and often "proof of concepts" for Product enhancement and future capabilities ## Related Videos - [Alibaba Big Data and Machine Learning Technology](https://www.wearedevelopers.com/videos/37-alibaba-big-data-and-machine-learning-technology) - [Introduction to TXT](https://www.wearedevelopers.com/videos/30-introduction-to-txt) - [Data Science on Software Data](https://www.wearedevelopers.com/videos/162-data-science-on-software-data) - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [PySpark - Combining Machine Learning & Big Data](https://www.wearedevelopers.com/videos/44-pyspark-combining-machine-learning-big-data) - [Implementing continuous delivery in a data processing pipeline](https://www.wearedevelopers.com/videos/73-implementing-continuous-delivery-in-a-data-processing-pipeline) ## Related Articles - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [Top Big Data Technologies That You Need to Know](https://www.wearedevelopers.com/magazine/108-top-big-data-technologies-that-you-need-to-know) - [What Industries Outside of AI Are Hiring The Most AI Experts?](https://www.wearedevelopers.com/magazine/98-what-industries-outside-of-ai-are-hiring-the-most-ai-experts) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [How to start an AI project for a good cause and boost your career](https://www.wearedevelopers.com/magazine/15-how-to-start-an-ai-project-for-a-good-cause-and-boost-your-career)