Job description

Since Resonate's founding in 2008, the company has been driven by a simple but powerful idea: understanding people. Resonate empowers leading brands and agencies with deep consumer intelligence that ignites unbreakable relationships through better connections, more meaningful engagement and compelling customer experiences. We are people-centric. It is at the heart of what we do and drives how we operate. We reveal the Human Element—a holistic understanding of a person that starts with what makes us the most human—our values and motivations. In other words, we help you understand the what that drives the why people decide to choose, buy, endorse or abandon a brand or cause. By combining this human, person-based why with relevant data about your industry, brand or product, we help you create powerful marketing engagement that drives results. We are seeking a data scientist with operational experience developing and deploying gradient boosting algorithms. Reporting directly to the Vice President of Data Science and AI, the successful candidate will play a key role in our data science initiatives and work closely with a dedicated team of machine learning engineers. The ideal candidate should have a strong foundation in probability/statistics, gradient boosting algorithms, and ML Ops. This role involves developing and implementing machine learning models, managing the deployment process, ensuring the models' scalability and security, and accommodating model drift. At Resonate, we celebrate diversity and are committed to creating an inclusive environment for all employees. We believe that a variety of perspectives and backgrounds foster innovation and enhance our ability to deliver outstanding services and solutions. We welcome applicants of any race, color, religion, gender identity or expression, sexual orientation, national origin, genetics, disability, age, veteran status, and other diverse backgrounds and beliefs. Our commitment to diversity and inclusion is rooted in our company's core values and is reflected in our policies, programs, and practices. We strive to maintain a workplace where everyone's contributions are valued, and where every employee has the opportunity to grow and achieve their full potential. Job Description: Resonate has developed a unique AI ecosystem built around a first-of-its-kind deep foundation model of consumer intelligence. In this role, you be at the forefront of extracting valuable insights from a vast array of online and offline data signals. You will drive innovation by developing a machine learning interface that leverages the power of foundation models to solve a myriad of tasks in predictive analytics – segmentation, forecasting, and classification. This is a unique opportunity to be at the forefront of building the next generation of enterprise level machine learning systems. Your contribution will be crucial in meeting the diverse data needs of various markets, including health, finance, consumer goods, politics, and advocacy. Leveraging cutting-edge data science techniques, you will identify trends, interpret complex data, and provide data-driven recommendations that directly impact key business decisions. At Resonate, we foster a culture of innovation and expect you to play an integral part in advancing our product suite, spanning from data development to software-as-a-service (SaaS) tools. You will be encouraged to challenge the status quo, introduce new tools and techniques, and bring forward fresh ideas that drive our mission forward. We are seeking a skilled data scientist. The ideal candidate will possess a strong theoretical understanding of gradient boosting methods and practical experience in applying these methods to real-world problems. You will be responsible for developing and deploying machine learning models capable of solving complex business problems. If you are passionate about data, possess a keen eye for detail, and have an unwavering commitment to innovation, we invite you to join our team and help shape the future of our company. Responsibilities and Duties: Build and deploy machine learning models to solve complex business problems. Apply advanced statistical and predictive modeling techniques to build, maintain, and improve on multiple real-time decision systems. Use gradient boosting frameworks such as XGBoost, LightGBM, CatBoost, and related technology to build and train models. Collaborate with other Data Scientists as well as Data and ML Engineers to develop data and model pipelines Assist in deploying models into production and monitor their performance with high governance standards Identify and recommend new applications of machine learning across the organization. Conduct research and analysis to identify novel applications of machine learning across the organization. Make recommendations on ML best practices, tools, and standards. Collaborate with the Product organization to develop novel products and solutions Improve business processes through data-driven insights. Provide insights and suggestions for process improvements. Understand business needs to guide the development of effective data models Adhere to ethical principles in machine learning. Understand and adhere to ethical implications of model development and data usage, ensuring fairness and avoiding bias. Qualifications: Strong foundation of statistics, probability, and mathematics Demonstrated proficiency with at least one of the following: XGBoost, LightGBM, CatBoost, SageMaker Pipelines (or other cloud providers for ML development and orchestration) Demonstrated experience with hyperparameter tuning libraries including Optuna, Hyperopt, or other autoML methods. Demonstrated experience with Machine Learning Ops, including deployment and management of models in production. A scientific mindset: The ability to solve problems through a combination of deep research, experimental design, hypothesis testing, and analysis. This skill requires the ability to think critically about vague or impossible problems, identify patterns, and draw conclusions. It also requires the ability to be open-minded and willing to challenge existing assumptions. Exceptional communication and collaboration skills with the ability to explain complex topics to a non-technical audience. Continual learning mindset to stay current with the latest deep and machine learning trends. Prior experience working closely with business stakeholders to understand and fulfill requirements. Education and Experience: At least 2 yrs experience with gradient boosting algorithms and associated hyperparameter tuning methods or a cloud ML platform like SageMaker. At least 1 year of professional experience in a data science, machine learning engineering, or software development role. A bachelor's degree in a relevant field; advanced degrees perferred. A track record of deploying ML models and deriving solutions from data. This job description outlines the general nature and level of work performed by employees within this role. It is not designed to contain or be interpreted as a comprehensive inventory of all required duties, responsibilities, and qualifications. Employees may be assigned additional responsibilities as necessary. Benefits Besides the opportunity to work with smart, fun, hard-working Resonate employees, you will have uncapped growth potential, a work/life balance, and a competitive suite of benefits. Location At Resonate, we're proud to offer a flexible work environment that combines the best of both worlds. Our team is made up of talented individuals who collaborate seamlessly across physical locations, thanks to our innovative hybrid and remote work policies. Whether you're working from home or from one of our state-of-the-art offices, you'll have access to the tools and resources you need to succeed. Resonate is headquartered in Reston, VA with offices in New York City, and Washington, D.C. Be a part of the team that changes the industry! Our EEO Statement: Resonate is an equal opportunity employer that is committed to diversity and inclusion in the workplace. We prohibit discrimination and harassment of any kind based on race, color, sex, religion, sexual orientation, national origin, disability, genetic information, pregnancy, or any other protected characteristic as outline by federal, state, or local laws. Find out more about our story at . #J-18808-Ljbffr

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