Johannesburg: Job Description: Sales Director – Africa – Remote/Hybrid

Job Description: Sales Director Africa Remote/Hybrid Our client is a fast-growing Enterprise AI software company for Financial Services. Their next generation AI platform automates the entire life cycle of data science and machine learning. It helps organizations to rapidly develop, deploy, manage, govern and operationalise AI applications at scale, ethically & responsibly. Our product is designed to develop highly accurate, trusted & explainable models and deploy advanced machine learning/deep learning models in production, with just a few clicks. It is a zero-code platform with real time scoring and monitoring of model performance. Our client helps organisations accelerate their AI journey and enables AI based solutions in hours and days instead of weeks and months, accelerating the return on investment of AI projects. Their no-code platform augments the capability of data science teams, empowering them to be faster, more consistent and accurate and to focus on solving business problems rather than coding. Offices: Headquarters in Bangalore, India with offices in USA and South Africa. About the Role: Designation: Sales Director: Africa Location: Prefer Johannesburg / Cape Town Experience: 8 years platform sales experience in Financial Services, with experience in data science. Reports to: EVP: EMEA Job Description: Our client is seeking a Sales Director for our zero-code AI platform which offers end-to-end data science and machine learning (DSML) solutions to financial services organisations. The Sales Director: Africa will lead and drive revenue growth for the companys platform solutions. This role requires a strategic thinker with a strong background in enterprise sales, SaaS, and platform-based business models. The ideal candidate will have deep expertise in the analytics and ML domain, including the ability to engage with clients, understand their business challenges, and present tailored solutions. The successful candidate will develop and execute sales strategies, build key client relationships and drive platform adoption and revenue. Roles & Responsibilities: Sales Strategy and Execution: Develop and implement a comprehensive sales strategy to achieve revenue targets. Identify and pursue new business opportunities across Financial Services businesses (banks, insurers, lenders and Fintechs). Work cross-functionally with Product, Marketing, Pre-Sales and Customer Success teams to ensure delivery of sales goals and company objectives. Understand customer pain points and articulate how the platform addresses business challenges. Lead contract negotiations and deal structuring to close high-value agreements. Proposal & Bid Management: Work with the Pre-Sales and Product teams to: Build and maintain strong relationships with enterprise clients. Create comprehensive and compelling AI platform proposals, including solution approach, costs, scope and timelines. RFP responses, ensuring alignment with client requirements and company capabilities. Coordinate with internal teams to ensure that proposals are delivered on time, within budget, and meet quality standards. Revenue Growth & Forecasting: Own and manage sales pipeline, forecasting, and revenue reporting to leadership. Utilize data-driven insights to optimize sales performance and identify growth opportunities. Qualifications & Experience: Education : Bachelors degree in Computer Science, Engineering, Data Science, or related field. Alternatively, a Batchelors degree in Business with extensive Data Science or related experience. Experience: Technical Skills: Soft Skills: 8 years of experience in the field of data science, or machine learning with at least 5 years in a Sales role. Proven track record of leading successful platform sales cycles for complex solutions, with a deep understanding of the sales process. Strong understanding of data engineering, data analytics, artificial intelligence, and machine learning technologies. Strong domain knowledge in developing credit risk scorecards, debt collection scorecards, customer acquisition scorecards etc. for financial services. Deep knowledge in analytical solutions, predictive modeling, and building analytics pipelines for banking or insurance. Strong knowledge of big data technologies, cloud platforms (AWS, Azure, GCP), and analytics tools. Familiarity with emerging trends in artificial intelligence, deep learning, NLP, and automated machine learning. Excellent communication skills, both verbal and written, with the ability to present to executives and technical teams. Strong problem-solving skills, with the ability to think creatively and propose innovative solutions. Strong business acumen, with the ability to translate technical capabilities into business value. Ability to handle complex, high-pressure situations and drive multiple opportunities to successful closures.