Job Application for Senior Data Scientist at Resonate

Resonate’s Data Science team is on a mission to push the boundaries of AI-driven consumer insights, delivering best-in-class, privacy-conscious, and scalable predictions. We leverage cutting-edge technologies to turn data into high-quality predictions that shape the future of consumer understanding. As an AI-first data company, our data scientists are both creators and champions of the power of AI—driving innovation internally and inspiring external stakeholders.

We’re seeking a Senior Data Scientist who combines deep expertise with a passion for learning, teaching, and delivering transformative products. They need to have hands-on experience developing and deploying neural networks at scale. This role will report directly to the Vice President of Data Science and AI and collaborate closely with a talented team of machine learning engineers to drive our data science initiatives forward.

Job Description:

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 expertise will contribute to solving complex, industry-specific problems across health, finance, consumer goods, politics, and advocacy. Domain-specific experience in any of these areas is a plus, as it helps us better understand unique market challenges and craft targeted machine learning solutions. 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. 

 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. 

Key Responsibilities:

Build and deploy machine learning models to tackle complex business challenges, particularly in predictive analytics, segmentation, forecasting, and classification.
Apply advanced statistical and predictive modeling techniques to create and enhance real-time decision systems.
Work alongside fellow Data Scientists and ML Engineers to develop robust data and model pipelines, ensuring seamless integration and efficiency.
Assist in deploying models into production and monitor their performance while adhering to high governance standards.
Identify and recommend new machine learning applications within the organization, conducting research to uncover novel use cases.
Collaborate with the Product organization to create innovative products and solutions that meet business needs.
Understand and adhere to ethical principles in machine learning, ensuring fairness and mitigating bias in model development.

Qualifications:

Strong foundation in statistics, probability, and mathematics, with demonstrated proficiency in at least one of the following: TensorFlow, PyTorch, or JAX.
Proficient in Python and familiar with R (or a willingness to learn).
Proven experience in Machine Learning Ops, particularly in deploying and managing models in production environments.
A scientific mindset with the ability to solve problems through research, experimental design, hypothesis testing, and analysis. This includes the capacity to identify patterns, draw conclusions, and challenge existing assumptions.
Exceptional communication and collaboration skills, enabling you to explain complex concepts to non-technical audiences effectively.
A commitment to staying updated on the latest trends in deep learning and machine learning.

Education and Experience:

At least 8 years of experience in machine learning, with deep expertise in deploying neural networks and an interest in causal inference and Bayesian methods (familiarity with causal inference is a plus).
At least 2 years in a managerial role, demonstrating leadership skills and the ability to mentor junior data scientists while fostering a collaborative environment.
A minimum of 2 years of experience engaging with customers.
A bachelor’s degree in a relevant field; advanced degrees are preferred.
Proven success in deploying machine learning models and deriving actionable insights 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 www.resonate.com. 

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