Senior Data Scientist II

At Talkdesk, we are courageous innovators focused on redefining the customer experience, making the impossible possible for companies globally. We champion an inclusive and diverse culture representative of the communities in which we live and serve. And, we give back to our community by volunteering our time, supporting non-profits, and minimizing our global footprint. Each day, thousands of employees, customers, and partners all over the world trust Talkdesk to deliver a better way to great experiences.

We are recognized as a cloud contact center leader by many of the most influential research organizations, including Gartner and Forrester. With $498 million in total funding, a valuation of more than $10 Billion, and a ranking of #16 on the Forbes Cloud 100 list, now is the time to be part of the Talkdesk legacy to help accelerate our success in a new decade of transformational growth.

At Talkdesk, we embrace FAST, our fundamental operating principles that define who we are as an organization. These principles drive us to make the impossible possible. FAST: Focus + Accountability + Speed = Talkdesker.

• Focus: Focus time, energy and attention on what is most impactful for the business and thoughtful about how and when to partner with others.
• Accountability: Hold self and others accountable to meet commitments and drive results. Accept responsibility for successes and failures.
• Speed: Execute with agility and urgency. Act promptly, decisively, and without delay. Make good and timely decisions that keep the organization moving forward.
• Talkdesker: YOU!

Role Summary: We are looking for a highly technical AI Engineer to join our People Team and accelerate our journey to become an AI-first organization. In this role, you’ll be at the heart of transforming how our People function operates by taking repetitive, manual processes and replacing them with AI-powered, scalable solutions. Your work will directly improve how thousands of employees experience their careers here, while showcasing what it means to run a truly AI-driven People function.

As a mid-level individual contributor, you will design and maintain the data architecture, pipelines, and integrations that consolidate people data from multiple systems into a centralized analytics environment. In your first year, your priority will be building a robust data foundation — ensuring clean, well-structured, reliable data that powers analytics and future AI applications. From there, you’ll expand into automation and machine learning solutions — for example, predictive models or AI-driven tools that elevate HR decision-making.

This role is highly collaborative, partnering with the People Analytics team, IT data engineers, PBPs, and external vendors or consultants to bring advanced technology to life within the People function.

Key Responsibilities:

• Data Pipeline Development: Build and manage scalable data pipelines to extract, transform, and load (ETL/ELT) people data from all our HR systems (Workday, Greenhouse, Peakon, Workramp, etc.) into a central data repository (Snowflake). Ensure data from different sources is properly connected (e.g. linking recruiting data to employee records) to enable holistic analysis. For example, you will design and develop people analytics data models and pipelines that provide efficient reporting across global HR stakeholders. This includes scheduling and orchestrating workflows, writing efficient scripts to transform data, and embedding data validation checks and alerting for data quality.
  
  
• Data Architecture & Modeling: Define the architecture for our People Analytics data environment. Structure a data warehouse or data lake that organizes HR data (e.g. employee demographic data, recruitment funnel data, performance scores, engagement survey results) in a logical, query-friendly manner. Develop and maintain dimensional data models and tables that support analytics needs (e.g. fact tables for headcount, snapshots for historical trend analysis). Ensure that the data architecture can scale with growth and accommodate new data sources or changes in HR processes.
  
  
• Data Integration & Quality: Work closely with IT and system owners to implement data integration solutions (APIs, scheduled exports, etc.). Monitor data flows to ensure timely and accurate updates. Implement robust data quality controls – for instance, building validation rules, anomaly detection, and notifications when data is incomplete or inconsistent. The goal is to deliver a reliable dataset for analysis with minimal manual intervention. Data quality and scalability with minimal manual work (DevOps) should be a hallmark of your solutions.
  
  
• Analytics & Reporting Enablement: Collaborate with People Analyst(s) to understand their data needs and optimize data structures for reporting (e.g. in Looker). Create documentation and maintain definitions for the data (e.g. data dictionary) to ensure consistency. Where helpful, develop automated data views or queries that analysts and People partners can use for self-service reporting. You may also build or support the enhancement of data visualizations and dashboards in our BI tools to surface key metrics.
  
  
• Automation of HR Processes: Identify opportunities to streamline, enable self-service, and automate manual processes in the People Ops realm. This could include building scripts or small applications to automate data transfers between systems (for example, automating a daily sync of new hires from Workday to downstream systems), generating routine reports or audit logs, or using robotic process automation (RPA) or scripts to eliminate repetitive administrative tasks. Work with HR process owners to prioritize automations that save time and reduce errors.
  
  
• AI and Machine Learning Projects: As the data foundation matures, lead experimentation with Ai/ML solutions to address HR needs. Develop predictive models or algorithms on people data (for example, flight risk predictions, quality of hire, performance prediction, skills/career path recommendations, etc.). Use appropriate machine learning libraries or tools to prototype solutions. Given our focus on employee feedback, you might also apply natural language processing (NLP) to analyze open-ended survey comments or other text data for sentiment and themes. Evaluate the feasibility of Ai tools in areas like resume screening, chatbot assistants for HR, or personalized learning recommendations – working closely with the Director to align these projects with strategic goals. (Note: We are open to either building these solutions or integrating third-party Ai vendors, so you will also partner to research and recommend vendor tools where appropriate.)
  
  
• Collaboration & Consulting: Work in tandem with IT data and InfoSec teams to align on data architecture and adhere to company-wide data security practices. Collaborate with the People Analytics Team to understand business questions and ensure the data is structured to answer them. Provide technical expertise in conversations about new HR tech vendors – for example, assessing how our applicant tracking platform could integrate with our warehouse, or how to export data for analysis. Assist in scoping and implementing any Ai/analytics vendor solutions we might purchase, ensuring that data flows and outcomes meet our requirements.
  
  
• Continuous Improvement & Innovation: Stay up-to-date on emerging technologies in data engineering, analytics, and Ai (especially in the HR domain). Introduce best practices for code management, documentation, and reproducibility. Build reusable frameworks and pipelines that can be leveraged by others on the team, thereby accelerating future development. Always be on the lookout for new tools or methods (for instance, improvements in Workday’s data analytics capabilities or new open-source ML tools) that could enhance our People Analytics capabilities.

Qualifications/Skills:

• Education & Experience: Bachelor’s degree in Computer Science, Data Engineering, Analytics, or related field. Approximately 4-6 years of hands-on experience in data engineering or analytics development (experience in HR/People data is a plus).
  
  
• Data Engineering & Programming: Strong skills in SQL and at least one programming language for data processing (e.g. Python, R, or similar – we are flexible with the specific language). Experience building ETL/ELT pipelines in a professional setting – including data extraction via APIs or database queries, transformation (using scripts or tools like dbt), and loading into data warehouses. Familiarity with cloud data platforms and tools (e.g. AWS Redshift, Google BigQuery, Snowflake, etc.) and orchestration frameworks are highly desirable.
  
  
• Analytics & BI Tools: Experience working with BI/analytics tools and frameworks. Ability to structure data for reporting and to understand how analysts will use the data (experience with Looker, Tableau, or similar data visualization tools is a plus). Basic understanding of statistics or data analysis techniques; ability to collaborate with data analysts and comprehend their needs.
  
  
• Machine Learning Knowledge: Foundational knowledge of machine learning techniques and libraries (such as scikit-learn, TensorFlow, or NLP libraries) is preferred. While deep expertise is not required initially, the role will involve growing into advanced analytics – so curiosity and ability to learn new Ai/ML tools is important. Any experience building predictive models or analytics solutions in HR (e.g. attrition models, survey text analysis) would be an advantage.
  
  
• Automation & Scripting: Proven ability to automate tasks using scripts or programming. Experience integrating systems or using APIs to connect tools. Comfort with handling data in various formats (CSV, JSON, etc.) and troubleshooting data issues.
  
  
• Collaboration & Communication: Good communication skills to work with non-technical stakeholders. Ability to translate complex technical concepts into layman’s terms when needed. A collaborative mindset – ready to work closely with People team members, understand business processes, and tailor solutions accordingly.
  
  
• Problem-Solving: A self-starter who can proactively identify problems or inefficiencies and develop technology solutions to address them. Strong analytical and problem-solving capabilities, with attention to detail and a commitment to data accuracy.
  
  
• Adaptability: Willingness to adapt in a fast-paced, changing environment. Our team is experimenting with cutting-edge approaches, so the engineer should be comfortable with ambiguity and rapid learning. Demonstrated ability to research new technology areas and innovate to produce the best results with people data.
  
  
• Global/Remote Collaboration: Experience working in distributed teams or with colleagues across different regions/time zones is a plus.

Work Environment and Physical Requirements:

Primarily office-environment work, extended periods of sitting or standing, computer-based work. Limited lifting, and equipment usage limited to computer-related equipment (keyboards, mouse, etc.)

The Talkdesk story hinges on empathy and acceptance. It is the shared goal among all Talkdeskers to empower a new kind of customer hero through our innovative software solution, and we firmly believe that the best path to success for our mission is inclusivity, diversity, and genuine acceptance. To that end, we will hire, promote, work along, cheer for, bond with, and warmly welcome into the Talkdesk family all persons without regard to ethnic and racial identity, indigenous heritage, national origin, religion, gender, gender identity, gender expression, sexual orientation, age, disability, marital status, veteran status, genetic information, or any other legally protected status.