Address
Form of work
SalarySenior Data Scientist | US
Chicago Hybrid (preferred); or Remote in CT/ET time zones
About Us!
Kooth is a fast-growing organization with an aim to create a welcoming space for effective, personalized digital mental health care, accessible to all. After 20 years of successful services in the UK, we are rapidly expanding in the United States.
Our platform is clinically robust and accredited to provide a range of therapeutic support and interventions. All our services are predicated on easy access to make early intervention and prevention a reality. Kooth is a fully safeguarded and pre-moderated community with a library of peer and professional created content, alongside access to experienced online counselors. There are no thresholds for support and no waiting lists.
OUR MISSION: To provide welcoming and effective digital mental health support to students proactively.
The Data Science team at Kooth aims to build human-centered, ethical machine learning products and features. As part of the Engineering Team, Data Scientists closely collaborate with software engineers, product managers, designers, and delivery leads.
We are currently growing our US Data Science presence in order to meet the growing needs of our organization to deliver mental health services safely and at scale. It’s an exciting time to join us
This role is open to remote work in the Central Time and Eastern Time zone, standard business hours (9am-5pm).
Chicago Hybrid (preferred); or Remote in CT/ET time zones
Preference will be given to candidates who are willing to work at our Chicago office between 1-3 working days per week.
Valid U.S. Work authorization is required for this position. No H1NB, nor C2C will be considered.
Primary Responsibilities include:
Architecture design of machine learning systems: appropriate algorithms, models, and frameworks to use, ensuring scalability, reliability, and sufficient performance
- Take a human-centered approach to identifying opportunities for data science to be used as a resource for Kooth’s product innovation – and making sure we’re solving the right problems in the first place
- Lead development, training, and validation of machine learning models for product innovation
- Monitor and optimize models in production
- Ensure privacy and security measures are in place, minimize bias and fairness issues in models, and adhere to ethical guidelines and regulations Establish and maintain coding standards, for example, by providing and receiving constructive feedback to improve the overall quality of machine learning code
- Share expertise, provide guidance, and help develop the technical skills of others i.e. pair-program alongside fellow Data Scientists and engineers, and learn best practices from them as well
- Participate in code reviews to ensure code quality, maintainability, and adherence to best practices
- Stay updated with the latest advancements in data science and related fields to inform our ML strategy and practices Work closely with cross-functional teams, such as software engineers, product managers, delivery leads, designers/UX researchers, and other stakeholders, to understand requirements, provide technical guidance, and ensure successful delivery of machine learning products and features
- Communicate complex technical concepts to non-technical audiences
- Collaborate with stakeholders to identify opportunities to apply data science across the organization
Ideal candidate traits include:
- the ability to self-manage their own projects, priorities, and deadlines
- exceptional communication skills, both written and verbal, with a strong ability to articulate ideas effectively through presentations and written communication
- Loves using math to solve problems
- Is not afraid to learn something new
- Is creative and willing to think out of the box
- Strives to be an excellent and versatile computer programmer
- Is interested in aligning with our purpose and values
- Has a combination of real-world experience and formal education, enabling them to bring a valuable blend of data science expertise and practical skills to the role
What you will bring:
Please submit your Cover Letter (we actually read them!) and Resume.
In your Cover Letter, please include your answer to this question:
- What excites you about working in data science at Kooth?
We don’t have a specific minimum requirement for educational degrees or years of work experience, but we’ve observed that people who excel in some of the skills we list above – specifically technical leadership, communication, and collaboration – have usually developed those skills through a university degree and work post education.
Thus, successful candidates tend to have full time work experience after having obtained a bachelor’s or PhD degree, and may also include experience in community organizations, graduate-level academic research, open-source software projects, or something else.
We're eager to hire people who believe in our mission and who will contribute to our team in a variety of ways - not just candidates who check all the boxes. In fact, we’re often most excited about people from professional backgrounds adjacent to data science. So, if you’re excited about us and can see yourself in the role, even if you don't feel that you meet every single requirement, we still encourage you to apply.
Compensation: $160,000-180,000 as aligned with skills & experience.
Here are some of the exciting benefits you will receive as a team member at Kooth:
- Excellent Medical, Dental and Vision benefits
- Prescription drug coverage
- Generous paid time off
- 8 paid holidays plus two, half-day holidays (Christmas Eve and New Years Eve)
- 401(k) retirement plan
Kooth provides equal employment opportunities to all people without regard to race, color, national origin, ancestry, citizenship, age, religion, gender, sex, sexual orientation, gender identity, gender expression, marital status, pregnancy, physical or mental disability, protected medical condition, genetic information, military service, veteran status, or any other status or characteristic protected by law.
