About careerzynith
careerzynith is a forward-thinking, innovation-driven organization that believes in the transformative power of data. As a global leader in workforce solutions and talent acquisition, careerzynith partners with companies across diverse industries to help them hire, develop, and retain the best talent in the world. At the heart of our mission lies a commitment to leveraging cutting-edge analytics, machine learning, and statistical modeling to revolutionize how organizations understand and engage their workforce.
Our Talent Acquisition (TA) Analytics team sits at the intersection of data science, human resources, and business strategy. We are the trusted partners to recruiters, hiring managers, and business leaders, providing them with the insights they need to make smarter, faster, and more equitable talent decisions. As we continue to grow, we are investing heavily in rebuilding our analytics capabilities from the ground up — and that is where you come in.
Position Overview
We are seeking an experienced, intellectually curious, and highly motivated Senior Data Scientist – Talent Acquisition Analytics & People Insights to join our dynamic team. In this role, you will be a key driver of our data and analytics transformation, designing, building, and deploying scalable solutions that influence how talent flows into and through careerzynith. From candidate sourcing and pipeline optimization to predictive modeling of candidate success, your work will directly impact the quality and efficiency of every hire we make.
This is not a role where you will simply generate reports or maintain dashboards. You will be hands-on with data, building machine learning models, designing experiments, automating processes, and presenting findings to senior leadership. If you are passionate about using data to solve real-world business problems, enjoy working in a fast-paced, collaborative environment, and want to make a tangible difference in how organizations build their workforce, this is the opportunity for you.
Key Responsibilities
- Partner closely with talent acquisition leaders, human resources business partners, software engineers, and senior executives to deeply understand business processes and identify high-impact opportunities for data science interventions.
- Source, clean, transform, and model large, complex datasets drawn from a variety of systems, including applicant tracking systems, HRIS platforms, CRM tools, and external labor market data providers.
- Design, develop, and rigorously evaluate machine learning and statistical models that address specific business questions such as candidate quality prediction, time-to-fill forecasting, sourcing channel effectiveness, and employee retention modeling.
- Build scalable, efficient, and automated data pipelines that power client-facing reporting tools, executive dashboards, and self-service analytics capabilities for non-technical stakeholders.
- Automate key talent acquisition processes using scripting, orchestration tools, and machine learning to streamline operations and reduce manual effort for the recruiting team.
- Define and execute A/B tests and other experimental designs to measure the impact of new sourcing strategies, interview processes, and candidate engagement initiatives.
- Identify, evaluate, and implement emerging trends in data warehousing, data engineering, and analytics tooling — including modern cloud-native platforms, distributed computing frameworks, and visualization technologies — to keep careerzynith at the forefront of the field.
- Proactively manage multiple, often interdependent, projects simultaneously, balancing competing priorities while maintaining a sharp focus on delivering high-quality, actionable insights.
- Communicate complex analytical findings clearly and persuasively to both technical and non-technical audiences through verbal presentations, written reports, interactive dashboards, and storytelling with data.
- Evangelize successful analytical projects and best practices across the broader organization, helping to foster a data-driven culture within talent acquisition and beyond.
- Champion data quality, governance, and ethical AI practices in all aspects of your work, ensuring that our models are fair, transparent, and compliant with applicable regulations.
Essential Qualifications
- Bachelor's degree in a quantitative discipline such as Statistics, Mathematics, Data Science, Business Analytics, Economics, Finance, Engineering, Computer Science, or a related field.
- 3+ years of hands-on professional experience with data querying languages (such as SQL), scripting languages (such as Python), and statistical or mathematical programming environments (such as R, SAS, Matlab, or equivalent).
- 3+ years of applied experience with machine learning and statistical modeling techniques, including supervised and unsupervised learning methods, and a deep understanding of the parameters that influence model performance.
- Demonstrated experience translating theoretical statistical or machine learning models into practical, real-world applications that deliver measurable business value.
- Strong analytical and problem-solving skills, with the ability to break down complex, ambiguous business problems into structured, data-driven solutions.
- Excellent verbal and written communication skills, with a proven ability to translate technical concepts into clear, actionable recommendations for business audiences.
Preferred Qualifications
- Master's degree or PhD in a quantitative field such as Statistics, Mathematics, Data Science, Business Analytics, Economics, Finance, Engineering, or Computer Science.
- Prior experience working as a machine learning engineer or data scientist at a large, fast-paced technology company or a leading research-driven organization.
- Experience with cloud platforms such as AWS, Azure, or Google Cloud, and modern data warehousing technologies such as Snowflake, Redshift, BigQuery, or Databricks.
- Familiarity with natural language processing (NLP) techniques, including text classification, sentiment analysis, and named entity recognition, particularly as applied to resumes, job descriptions, or candidate feedback.
- Experience working with talent acquisition, human resources, or people analytics datasets is highly desirable.
- Track record of publications, conference presentations, or contributions to open-source data science projects.
Skills and Competencies for Success
- Technical Mastery: Deep expertise in SQL, Python, and at least one statistical programming language, with the ability to write production-quality, well-documented code.
- Statistical Rigor: Strong foundation in probability, statistics, and experimental design, with the ability to apply the right method to the right problem.
- Business Acumen: Ability to quickly understand business context, identify high-impact questions, and connect analytical outputs to strategic outcomes.
- Curiosity and Continuous Learning: A genuine passion for staying current with the latest trends, tools, and research in data science, machine learning, and talent analytics.
- Collaboration and Influence: A team-oriented mindset with strong interpersonal skills and the ability to build trust and credibility with stakeholders at all levels of the organization.
- Storytelling with Data: The ability to craft compelling narratives using data, visualization, and structured communication that drive action and decision-making.
- Project Management: Strong organizational skills, with the ability to manage multiple projects, set realistic timelines, and deliver high-quality results on schedule.
Career Growth and Learning Opportunities at careerzynith
At careerzynith, we believe that our people are our greatest competitive advantage. When you join our team, you will be surrounded by some of the brightest minds in data science, talent strategy, and human resources technology. We are deeply committed to the professional and personal growth of every team member, and we offer a wide range of learning and development opportunities, including:
- Access to premier online learning platforms, conference attendance, and certification programs.
- Mentorship from senior data scientists and analytics leaders who are invested in your success.
- Opportunities to present your work to executive leadership and influence company-wide strategy.
- Participation in cross-functional projects that expand your business acumen and professional network.
- A clear career progression framework that rewards both individual contribution and team leadership.
Work Environment and Culture at careerzynith
careerzynith is more than just a workplace — it is a community of curious, collaborative, and purpose-driven professionals who are passionate about using data to make a real difference. We celebrate diversity, equity, and inclusion in all its forms, and we are committed to building a workplace where every team member feels valued, heard, and empowered to do their best work. Our culture is built on the principles of intellectual honesty, mutual respect, continuous learning, and shared success. Whether you are working from one of our modern office hubs or remotely from your home office, you will find that careerzynith is a place where great ideas thrive and great careers are built.
Compensation, Perks, and Benefits
careerzynith offers a comprehensive and competitive compensation and benefits package designed to support the health, well-being, and financial security of our employees and their families. While specific offerings may vary by location, our typical benefits include:
- Healthcare: Comprehensive medical, dental, and vision insurance coverage for employees and their eligible dependents.
- Retirement Plans: A robust retirement savings program with company matching contributions to help you build long-term financial security.
- Paid Time Off: A generous mix of vacation, personal time, sick leave, and paid holidays to help you recharge and maintain a healthy work-life balance.
- Equity Programs: Opportunities to participate in careerzynith stock or equity programs, allowing you to share in the long-term success of the company.
- Employee Discounts: Discounts on careerzynith products, services, and partner offerings.
- Educational Assistance: Tuition reimbursement and educational support programs to help you continue your learning journey.
- Professional Development: Dedicated resources, training budgets, and time for professional growth and skill-building activities.
- Parental Leave: Comprehensive maternity, paternity, and parental leave policies to support you through major life milestones.
- Employee Assistance Programs: Confidential counseling, wellness resources, and support services to help you navigate personal and professional challenges.
- Flexible Work Arrangements: Depending on your role and location, opportunities for remote work, flexible hours, and hybrid schedules.
- Employee Recognition: Formal and informal recognition programs that celebrate outstanding contributions and achievements.
- Transportation and Wellness Benefits: Depending on location, subsidies for commuting, parking, gym memberships, and wellness initiatives.
How to Apply
If you are a driven, talented, and curious data scientist looking to make a meaningful impact in the world of talent acquisition and people analytics, we want to hear from you. Bring your expertise, your passion, and your ideas to careerzynith, and help us shape the future of how the world's best companies hire and develop their people. This is your opportunity to join a team that values innovation, celebrates diverse perspectives, and is committed to helping you grow both personally and professionally.
Take the next step in your career — apply today and become a key part of the careerzynith story. We can’t wait to see what we will build together.