证券行业掀起AI竞赛！算法工程师成“香饽饽”

Core Viewpoint - The competition in the securities industry driven by DeepSeek has led to over 30 brokerages completing localized deployments and application updates, showcasing their financial technology capabilities, with talent being a crucial foundation [1][4]. Group 1: Demand for Algorithm Engineers - There is a growing demand for algorithm engineers in brokerages, with a notable shortage of AI-related talent, particularly in large brokerages [2][5]. - The average recruitment cycle for AI engineering positions is around 60 days, indicating a competitive hiring environment [2]. - The demand for traditional IT roles has decreased, with a shift towards AI, algorithms, and big data talent since 2023 [5]. Group 2: Salary Trends - Despite the talent shortage, salaries for algorithm engineers have not significantly increased, with current compensation levels showing a decline of approximately 20% to 30% compared to previous years [8][9]. - The median annual salary for AI leaders with over ten years of experience in first-tier cities is around 1.5 million yuan, while algorithm engineers with five years of experience earn a median of 600,000 yuan [8]. - The bonus structure for algorithm engineers has also decreased, with many now receiving bonuses equivalent to 1-3 months' salary, compared to 8-12 months in previous years [9]. Group 3: Recruitment Challenges - The recruitment of algorithm engineers is primarily concentrated in the top ten brokerages, with fewer than 20 firms actively hiring for these roles [12]. - The industry is increasingly seeking candidates who possess both technical skills and financial knowledge, making cross-industry transitions less common [11]. - The hiring cycle for algorithm engineers typically ranges from 3 to 6 months, reflecting the challenges in attracting talent [11]. Group 4: Strategic Focus on Financial Technology - Brokerages are increasingly focusing on the effectiveness and quality of financial technology investments rather than just speed, with larger institutions leading the way in developing in-house capabilities [12]. - Smaller firms tend to be more cautious in their R&D investments, often opting for established external solutions to drive innovation [12].