Data Science Hiring and Interview Process at Pegasystems
Pegasystems, commonly known as Pega, is a global software company founded in 1983, focusing on customer engagement and operational excellence solutions. The Cambridge-based company has become a leader in business process management and customer relationship management. The primary offering, Pega Infinity, acts as a comprehensive platform for businesses to create, implement, and improve applications, aiming to enhance customer experiences and streamline operational processes. The company utilises AI and data science throughout its platform to improve decision-making, automate processes, and provide personalised customer interactions. CISCO, HSBC, and Siemens are a few of their primary customers. In their latest iteration of Pega Infinity 23, the platform introduces over 20 new features, including generative AI-powered boosters to enhance efficiency. The Connect Generative AI feature enables organisations to quickly utilise generative AI with a plug-and-play structure for low-code development. AIM caught up with Deepak Visweswaraiah, vice president, platform engineering and site managing director, and Smriti Mathur, senior director and head of people, Pegasystems, India, to understand their generative AI play, hiring process and more. Pega has open positions for solutions engineers and senior software quality test engineers in Hyderabad and Bengaluru. Decoding Pega’s AI Ventures In their core platform, Pega Infinity, the organisation relies heavily on data science, which plays a critical role in analytics, insights generation, natural language processing (NLP), generative AI, and various other applications that drive functionalities such as real-time decision-making and personalised customer communications based on attributes. Data science also contributes significantly to the development of generative AI models, enhancing the overall intelligence of the platform. Its impact extends beyond the core platform to applications like customer service, one-to-one engagement, decision-making, sales automation, and strategic smart apps for diverse industries. Pega GenAI provides insights into AI decision-making and streamlines processes, such as automating loan processing. “The benefits of generative AI extend to developers and end-users, improving productivity through query-based interactions, automatic summarisation, and streamlined case lifecycle generation,” Visweswaraiah told AIM. End-users also benefit from realistic training scenarios using simulated customer interactions. Regarding proprietary foundational models, the organisation’s product architecture prioritises openness and flexibility. They support various language models, including those from OpenAI and Google. “In upcoming product versions, we are actively working to support and ship local language models to meet specific use case demands, focusing on accuracy, productivity, and performance in response to customer preferences for diverse capabilities,” he added. Interview Process The company follows a global hybrid working model, encouraging collaboration in the office while providing flexibility, with about 60% of the workforce attending the office around three days a week. This approach aims to attract talent globally, fostering a vibrant culture and hybrid working environment. In upskilling employees, technical competencies are crucial, and the company emphasises learning through its Pega Academy, offering online self-study training, live instructor-led courses, and online mentoring. Skill gaps are regularly assessed during performance reviews, providing learning opportunities through gateways and supporting external courses with an educational reimbursement policy. “For data science roles, we focus on the candidate’s ability to learn rather than specific data science skills,” Mathur told AIM. The company looks for individuals capable of extracting insights from data, making informed decisions, and building models for application in various use cases. Mathur further shared that the company emphasises the importance of understanding its problem-solving approach and creating deterministic models that consistently provide performant and real-world solutions. It encourages candidates to think from the customer’s perspective and avoid getting lost in vast amounts of data, highlighting the significance of models producing consistent and reliable answers. Work Culture The company emphasises diversity and inclusivity, fostering a culture centred on innovation and collaboration. It has been ranked as the best workplace for women by Avatar for five consecutive years. Pega values individuals who think independently, challenge norms and question the status quo to seek better solutions. The company encourages leadership and curiosity in approaching tasks, promoting an environment where employees are empowered to innovate. Compared to competitors, Pega’s work culture stands out due to the unique problems it addresses and its distinctive approach. Understanding the product architecture is crucial for employees, given the nature of the challenges they tackle. Pega’s ability to integrate technology into the platform is a significant differentiator, enhancing its capability to address complex issues. “With a focus on adapting to market changes, our mantra of being “built for change” reflects our commitment to staying dynamic and responsive to evolving needs,” concluded Mathur. So, if you want to join the dynamic community of Pega, check out the careers page here.
For data science roles, Pega focuses on the candidate’s ability to learn and adapt rather than specific tech skills.
For data science roles, Pega focuses on the candidate's ability to learn and adapt rather than specific tech skills. 
["Data Science", "Data Science Hiring", "Top Trend"]
["Top Trend", "data science", "GenAI", "OpenAI", "AI", "ML", "RAG", "NLP", "Data Science Hiring", "Aim", "analytics", "generative AI", "Data Science"]
["AI", "ML", "NLP", "data science", "analytics", "generative AI", "GenAI", "OpenAI", "Aim", "RAG"]
Shritama (she/her) is a technology journalist at AIM who is passionate to explore generative AI with a special focus on big techs, database, healthcare, DE&amp;I, hiring in tech and more.