Background. As artificial intelligence and AI-powered systems continue to grow, the role of data scientists has become essential in software development environments. Data scientists face challenges related to managing large volumes of data and addressing the societal impacts of AI algorithms, which require a broad range of soft skills. Goal. This study aims to identify the key soft skills that data scientists need when working on AI-powered projects, with a particular focus on addressing biases that affect society. Method. We conducted a thematic analysis of 87 job postings on LinkedIn and 11 interviews with industry practitioners. The job postings came from companies in 12 countries and covered various experience levels. The interviews featured professionals from diverse backgrounds, including different genders, ethnicities, and sexual orientations, who worked with clients from South America, North America, and Europe. Results. While data scientists share many skills with other software practitioners—such as those related to coordination, engineering, and management—there is a growing emphasis on innovation and social responsibility. These include soft skills like curiosity, critical thinking, empathy, and ethical awareness, which are essential for addressing the ethical and societal implications of AI. Conclusion. Our findings indicate that data scientists working on AI-powered projects require not only technical expertise but also a solid foundation in soft skills that enable them to build AI systems responsibly, with fairness and inclusivity. These insights have important implications for recruitment and training within software companies and for ensuring the long-term success of AI-powered systems and their broader societal impact.