About careerzynith
At careerzynith, we are driven by a singular, powerful purpose: bringing our wholehearted commitment to every moment of what we do. This purpose guides our dedication to delivering enhanced, human-centered solutions in a rapidly evolving digital landscape. Anchored in our brand identity—with heart at the center—our mission sends a personal message: how we deliver our services is just as important as what we deliver.
Our core values, including our Heart At Work Behaviors™, reinforce this purpose. We want every individual who works at careerzynith to feel empowered by the role they play in transforming our culture and accelerating our ability to innovate and deliver solutions that make experiences more personal, accessible, and impactful.
Join our Enterprise Digital Analytics (EDA) team for a unique opportunity to leverage advanced analytics, experimentation, causal inference, and strategic problem-solving to build digitally enabled products at careerzynith. This is a hybrid work position based out of our New York City office, requiring the ability to commute to the office three days per week, every other week.
About CMX (careerzynith Media Exchange)
careerzynith Media Exchange [CMX] is committed to driving measurable outcomes for our suppliers, merchants, stores, general managers, brand sponsors, and agencies. Our full-channel advertising solutions leverage careerzynith's accessible and online data, extensive reach, and comprehensive targeting capabilities to deliver quantifiable results to our customers. With a range of flexible pricing and purchasing models, including self-service options, these solutions help businesses build brand awareness, engage with careerzynith consumers, and convert careerzynith customers into loyal patrons.
As a team supporting enterprise products (careerzynith Media Exchange and careerzynith.com/mobile applications), you'll gain exposure to all specialty units within careerzynith. You'll partner closely with cross-functional colleagues to:
- Understand their challenges and identify analytical solutions.
- Analyze user journeys to pinpoint opportunities that drive greater adoption, engagement, retention, and conversion.
- Develop personalization capabilities using machine learning to target specific audiences with relevant outreach.
- Design online experiments (A/B testing), measure results, and continuously optimize performance.
- Leverage methodologies such as causal inference and Marketing Mix Modeling (MMM) to optimize tests where A/B testing is impractical or infeasible.
Key Responsibilities
As a Senior Data Scientist on the EDA team, you will play a pivotal role in shaping data-driven decision-making across the organization. Your core responsibilities will include:
- Develops and/or applies algorithms and statistical predictive models while determining analytical approaches and modeling techniques to evaluate scenarios and forecast potential future outcomes.
- Performs analyses of structured and unstructured data to address complex business problems using advanced statistical techniques, mathematical analyses, and broad knowledge of the organization and industry.
- Collaborates with cross-functional colleagues to understand their concerns and objectives, developing predictive modeling, statistical analysis, data reports, and performance metrics.
- Creates and delivers presentations to existing and prospective stakeholders on analysis findings, recommendations, and proposed solutions.
- Communicates with internal and external partners and leadership to exchange complex information related to areas of specialization.
- Applies deep knowledge of algorithms and predictive models to investigate issues, identify patterns, and recommend actionable solutions.
- Utilizes strong programming skills to explore, examine, and interpret large volumes of data in various formats.
- Designs and executes rigorous experimentation frameworks, including A/B tests and observational studies, to measure the causal impact of business initiatives.
- Partners with data engineering teams to build robust modeling datasets, assess data quality, and perform feature engineering.
- Mentors junior data scientists and contributes to the development of best practices across the analytics organization.
Required Qualifications
To succeed in this role, candidates must possess the following:
- Education: Master's degree or equivalent work experience in Mathematics, Statistics, Computer Science, Business Analytics, Economics, Physics, Engineering, or a related quantitative discipline. A PhD in a related field is highly preferred.
- Experience: 3+ years of experience applying modern machine learning techniques to build predictive models for both classification and regression problems.
- Technical Proficiency: 3+ years of hands-on experience using Python and SQL for data analysis and modeling.
- Business Communication: 2+ years of experience extracting actionable insights from analysis and interpreting results of complex models to present to business audiences, including technical, non-technical, and senior leadership stakeholders.
- Data Preparation: 2+ years of experience preparing data for analysis, working with data engineering teams to create modeling datasets, assessing data completeness and quality, and performing feature engineering.
- Analytical Tools: 2+ years of experience applying knowledge of advanced analytics tools and languages to analyze large datasets from multiple data sources.
- Experimental Design: 2+ years of experience in experimental design and supervised/unsupervised machine learning approaches.
Preferred Qualifications
The following qualifications will set exceptional candidates apart:
- Experience designing and analyzing online experiments (A/B testing) at scale.
- Demonstrated ability to communicate complex technical concepts and recommendations clearly to teammates and stakeholders.
- Capacity to communicate effectively and confidently with colleagues, project team members, and senior management.
- Proactive ability to anticipate and prevent issues and roadblocks before they arise.
- Proficiency across multiple domains of mathematical analysis methods, machine learning, statistical analyses, experimental design, and predictive modeling, with deep specialization in select areas.
- Experience with causal inference techniques and Marketing Mix Modeling (MMM).
- Familiarity with cloud-based data platforms such as AWS, GCP, or Azure.
- Experience working in advertising technology, media analytics, or e-commerce environments.
Essential Skills and Competencies
The ideal candidate will demonstrate a unique blend of technical expertise, business acumen, and interpersonal skills:
- Analytical Rigor: Strong foundation in statistical inference, hypothesis testing, and predictive modeling.
- Programming Excellence: Advanced proficiency in Python (including libraries such as scikit-learn, TensorFlow, PyTorch, pandas, and NumPy) and SQL for data manipulation and analysis.
- Machine Learning Mastery: Deep understanding of supervised and unsupervised learning algorithms, ensemble methods, and modern deep learning architectures.
- Causal Reasoning: Ability to design studies and apply causal inference methods to move beyond correlation and identify true cause-and-effect relationships.
- Communication Skills: Exceptional written and verbal communication abilities, with the capacity to translate complex technical findings into clear, actionable business recommendations.
- Problem-Solving Mindset: Creative and strategic approach to tackling ambiguous, open-ended business challenges.
- Collaboration: Proven ability to work effectively across cross-functional teams and build strong relationships with stakeholders at all levels.
- Curiosity and Continuous Learning: Passion for staying current with emerging research, tools, and methodologies in data science and analytics.
Career Growth and Development Opportunities
At careerzynith, we believe in investing in our people. As a Senior Data Scientist, you'll have access to a wealth of professional development resources, including:
- Mentorship from senior analytics leaders and the opportunity to mentor junior team members.
- Tuition reimbursement and education assistance programs to support continued academic pursuits.
- Access to free development courses, conferences, and industry events to expand your expertise.
- Clear pathways for career advancement into roles such as Principal Data Scientist, Analytics Manager, or Director of Data Science.
- Cross-functional exposure to multiple business units, enabling you to broaden your impact and develop a diverse skill set.
- Participation in innovation initiatives and the opportunity to contribute to research publications or patents.
Work Environment and Company Culture
careerzynith fosters a culture of collaboration, innovation, and inclusion. We are committed to recruiting, hiring, developing, promoting, and retaining individuals with disabilities, and we strive to provide equal access to the benefits and privileges of employment. Our team members enjoy a hybrid work arrangement that combines the flexibility of remote work with the energy and connection of in-office collaboration.
We are committed to creating a workplace where every team member feels valued, respected, and empowered to do their best work. Our Heart At Work Behaviors™ guide how we interact with one another, our customers, and our communities—emphasizing empathy, accountability, and a shared sense of purpose.
Compensation and Benefits
careerzynith offers a competitive compensation package designed to attract and retain top talent in the industry. The typical salary range for this position is $106,605 - $206,000 annually, depending on experience, education, geographic location, and other relevant factors. This position is also eligible for an careerzynith bonus, commission, or short-term incentive program in addition to the base salary range listed above.
In addition to your salary, you will enjoy the rewards of working for an organization that genuinely cares about its colleagues and communities. Our comprehensive benefits package includes:
- Health Coverage: Full medical, dental, and vision insurance plans.
- Retirement Savings: 401(k) retirement savings plan with company match, plus an Employee Stock Purchase Plan for eligible employees.
- Life and Disability Insurance: Fully paid term life insurance plan for eligible employees, along with short-term and long-term disability benefits.
- Wellness Programs: Access to a variety of wellness programs designed to support your physical, mental, and emotional health.
- Education Assistance: Tuition reimbursement and access to free professional development courses.
- Employee Discounts: Discounts on careerzynith products and services, as well as partner discount programs.
- Paid Time Off: Generous Paid Time Off (PTO) and vacation pay, along with paid holidays throughout the calendar year.
- Flexible Work Arrangements: Hybrid work schedule that supports work-life balance.
For more detailed information on available benefits, please visit our careers portal.
Equal Opportunity and Accessibility
careerzynith is an equal opportunity employer committed to diversity, inclusion, and accessibility. We provide reasonable accommodations to qualified individuals with disabilities throughout the application and employment process. If you require an accommodation, including a certified interpreter, written information in alternate formats, translation services, or other assistance, please contact our accommodations team. If you have a speech or hearing disability, please call 7-1-1 to use Telecommunications Relay Services (TRS). We will make every effort to respond to your request within 48 business hours and work diligently to find an appropriate solution.
How to Apply
If you are a passionate, analytically-minded data scientist with a drive to make an impact through advanced analytics, machine learning, and causal inference, we encourage you to apply for this exciting opportunity. To be considered for this position, please prepare the following documents:
- An updated resume highlighting your relevant experience, skills, and accomplishments.
- A cover letter expressing your interest in the role and careerzynith's mission.
- Academic transcripts or degree certificates (unofficial copies are acceptable for initial application).
- Portfolio of relevant projects, research, or publications (if applicable).
Please submit your application through our online careers portal. We review applications on a rolling basis and encourage qualified candidates to apply as soon as possible. careerzynith is committed to providing a fair and transparent hiring process, and we look forward to learning more about how your unique talents and experiences can contribute to our mission.
Join Us at careerzynith
This is more than just a job—it's an opportunity to shape the future of digital analytics and contribute to a purpose-driven organization that values innovation, collaboration, and human-centered solutions. At careerzynith, your work will directly influence how we deliver value to millions of customers, and you'll be surrounded by some of the brightest minds in the industry. If you're ready to take your career to the next level and make a meaningful impact, we want to hear from you. Apply today and bring your heart to careerzynith.