Moka, a Chinese start-up has received $27M investment led by Hillhouse to make the hiring process more data-driven in China. This is part of the company’s mission to improve the quality of hires and make them more efficient.

Moka aims to streamline the recruitment process by utilising data-driven insights to improve the hiring process. This article will discuss how Moka sets out to make this goal a reality.

Overview of Moka

Moka is a China-based recruitment technology startup using data-driven science and machine learning to improve hiring. Founded in 2018, Moka has grown from a team of three to nearly 100 and is backed by prominent investors such as Uphill Capital and IDG Capital.

At its core, Moka provides recruiters with the tools they need to make better decisions when it comes to hiring. This can include insights into a candidate’s skills, career trajectory, and how they will fit into the company culture. With the help of NLP technology, big data analytics and AI algorithms, Moka can provide real-time automated feedback and recommendations regarding recruitment, which helps companies make better hiring decisions quickly and easily.

Moka’s mission is to bring “data-driven thought leadership to the talent acquisition community in China”, allowing businesses access to high quality data science resources tailored specifically for recruiting needs. With their cutting edge approach combining traditional wisdom with advanced data-driven decision making practices, Moka promotes a modernised form of human resource management. Moreover since its launch in 2018, Moka has been praised across China for its pioneering use of ATS (Applicant Tracking System), automated interview platform and an ever growing array of features designed specifically for recruiters such as their comprehensive job market platform Jobseekers Hub.

Overview of Hillhouse Capital

Hillhouse Capital is a Chinese venture capital firm that provides capital, strategic advice and operational support to early-stage growth companies across technology, media and healthcare. Founded in 2005 by founders Zhang Lei, SD Shariq Yosufzai, Doug Ramundt and Maggel Jainazan, Hillhouse has built a reputation as an early-stage investor with the experience to nurture small businesses into successful entities in the Chinese marketplace. The firm is best known for investing in leading unicorns like Didi Chuxing, Meituan Dianping and Xiaomi Corporation.

Hillhouse strives to help create a more data-driven hiring process for companies in China by using deep artificial intelligence solutions at scale. This vision encourages transparency around recruitment goals and challenges for each company’s hiring requirements. With its AI platform “Moka”, Hillhouse gives companies the tools needed to make tracking of job openings easier while integrating data predictive analytics into their key decision turning points.

Moka helps companies measure performance on multiple criteria such as job satisfaction level of existing employees; ease of completion of each stage of the recruitment process; cost per hire; candidate engagement rate; and recruiting efforts efficiency. All this is possible with innovative technology solutions like natural language processing (NLP) applied to combine internal data sources with external web information sources such as social media sites like LinkedIn and Glassdoor to form comprehensive resumes quickly poll robust offline resources like audio files, interviews and transcripts.

Armed with AI solutions that can relieve time consuming manual tasks HR departments can analyse better understand their talent investments which Moka strive ultimately optimise create measurable changes across management processes inform organisations future actions HR professionals can trust the metrics leveraging from Moka ensure better results company’s efforts attract retain best talent within market conditions making mission envision.

Moka raises $27M led by Hillhouse to make hiring more data-driven in China

Moka has recently raised $27M led by Hillhouse to make hiring more data-driven in China. With this investment, the company plans to expand its AI-powered platform, Moka360, which helps companies make more data-driven decisions during the hiring process.

This article will discuss why this development is important and how Moka plans to make hiring more data-driven in China.

Moka’s mission to modernise the hiring process

Moka, a Chinese AI-powered talent platform, aims to make hiring practices more data-driven and transparent in China. Founded in 2018, Moka has developed an AI-powered platform that enables employers to better assess and shortlist their potential hires by leveraging the latest algorithms and predictive analytics.

Moka’s mission aims to make the traditional Chinese hiring process more efficient by removing outdated assumptions and discriminatory biases that could harm companies and jobseekers. By digging deeper into each candidate’s experience, skillset, potential impact on teams, salary expectations, education backgrounds and other characteristics– Maoke’s AI engines can better identify the best from the rest when selecting the ideal candidate for each role.

The company also offers a comprehensive suite of tools designed to help recruiters increase their success rate when sourcing new hires. These tools include applicant tracking tools for organising large volumes of applications, resume optimization services for creating interactive CVs uniquely tailored to the needs of employers. In addition, these pre-screening modules quickly evaluate candidates based on pre-defined criteria such as coding abilities or working language proficiency, intelligent job matching systems powered by natural language processing (NLP) technologies which automatically suggest potential fits between employee requirements and open positions, as well as predictive analytics platforms that provide theoretical suggestions about employee recruitment plans.

In addition to providing these platforms to recruiters in China – Moka is also making strides in addressing ageism in hiring practices through its companion app ‘Personal FaceUP’ which addresses discriminatory biases against older workers at the onboarding stage by supplying recruiters with age-neutralised profiles of job seekers before any interview takes place thus preventing skewed results due to biassed preconceptions. Alongside this, Moka also offers dedicated diversity consulting services to assist enterprises with understanding how best to create an inclusive workforce while still adhering to current employment regulations.

Hillhouse’s investment to help Moka reach its mission

Hillhouse Capital, one of China’s leading venture capital firms, recently invested in Moka. The company’s mission is to make hiring more data-driven in China. Moka helps companies use data to better assess and recruit top talent.

The investment will enable Moka to further expand its operations in China. It will also help Moka improve its technology and develop innovative products that can revolutionise how companies hire qualified employees.

Moka leverages various technologies including machine learning and natural language processing Artificial Intelligence (AI) for facial recognition and voice analysis, giving employers complete access to a large pool of candidates personalised for their organisation. In addition, this technology provides employers with a selection of candidates based on previous trends to help identify the best fit for each organisation’s requirements and values.

Hillhouse is confident that with this additional financing, Moka can continue its mission to lead the field in data-driven recruitment solutions, powering enterprises across all industries around China while helping hiring teams recruit top talent more efficiently than ever.

Benefits of data-driven hiring

In today’s global economy, data-driven hiring is becoming increasingly important. This type of hiring offers a range of benefits for employers, from better understanding of their talent pool and the ability to measure skills and performance to better match candidates to the right roles.

Moka, a Chinese startup, recently raised $27M led by Hillhouse to make hiring more data-driven in China, showing that data-driven hiring is becoming an increasingly popular approach.

Let’s look at the benefits of data-driven hiring in more detail.

Improved candidate experience

Data-driven hiring processes allow employers to create a more seamless and integrated recruiting experience for job seekers. By using automation, big data and analytics tools, companies can identify available talent pools quickly and efficiently. This enables them to reach out to potential candidates more quickly without sacrificing the quality of the candidate experience. Automated systems can also be integrated with social networks, allowing employers to find like-minded talent to build tailored and customised opportunities.

In addition, data-driven hiring processes foster a more transparent and stress-free recruitment process. Accessing real-time data helps recruiters better understand their candidates’ skillset, qualifications, interests and career goals. A comprehensive understanding of the requirements for each role allows recruiters to tailor their recruitment strategies accordingly and offer solutions that suit each candidate’s unique needs. Taking an individualised approach enables employers to save time as they can assess a larger pool of potential hires faster through technological processes – ultimately improving the time it takes between job opening postings and successful hires.

The increased speed and efficiency enabled through data driven recruitment solutions result in shorter time frames between job postings or applications and successful placements; this shortens perceived delay periods on the candidate’s side while improving communication, feedback loops, candidate engagement as well as overall satisfaction on both sides; this ultimately resulting in improved employer branding with higher ratings on online reviews while leading towards greater customer loyalty among potential applicants & boosting employer attractiveness on long run operations.

Improved employer decision-making

Data-driven hiring has the potential to help employers make more informed decisions about their recruitment process. By enabling them to apply scientific, fact-based decisions, data-driven hiring can improve the accuracy of the recruitment process. This can result in better employee retention, decreased time-to-hire, and an improved employer brand. Additionally, a data-driven approach to hiring can ensure effective hire outcomes by gathering qualitative and quantitative insights that accurately reflect the job seekers’ attributes and skills.

In addition to these benefits of improved employer decision making, data-driven hiring also offers strategic advantages including:

• Improved candidate engagement & experience — Employers who incorporate data into their hiring process can identify candidates likely to stay longer by understanding what motivates them. Consequently, they can effectively craft interview questions that will improve the candidate experience and focus on finding a great fit the first time around.
• Accessibility for remote workers — By leveraging technology optimised for remote working such as video interviewing tools and tools for onboarding employees remotely, data-driven hiring allows employers to access recruits from anywhere in China or abroad regardless of time zone or language barriers.
• Dynamic job market insights — Employers have access to real-time analytics on all steps of their recruitment process. This provides them with up-to-date insights into labour trends in China and recommendations for meeting those demands should they need it (e.g., increase wages or create more flexible contracts).

With these advantages combined, a data driven approach towards recruiting can provide employers a wealth of advantages when it comes to finding ideal candidates and better managing their workforce overall — making Moka’s mission even more compelling.

Challenges of data-driven hiring

With Moka’s mission to make hiring more data-driven in China, there will inevitably be some challenges along the way. One of the most significant challenges of data-driven hiring is ensuring the data collected accurately reflects the job requirements. Additionally, it can be difficult to ensure that the recruitment process is fair and unbiased to all applicants and that the privacy of candidates is respected and protected.

Let’s explore some of the other challenges of data-driven hiring.

Data privacy and security

Data privacy and security are paramount in China, as companies must comply with the extensive laws and regulations governing the use of data. For example, companies must have consent from candidates to process job applications, and any collected data must be used only for the purpose it was collected — namely, finding qualified employees. Additionally, all employee data should be securely stored and handled carefully to prevent misuse or potential accidental breaches.

Due to concerns from both employers and candidates over privacy, many companies struggle to utilise big data effectively in the recruiting process. Employers may be hesitant to collect detailed information about candidates but worry that making do without it could lead them to hire unsuitable workers. Candidates may also be reluctant to share personal information due to fears that their data may be misused by employers or could land in the wrong hands. Finding a balance between collecting necessary information and protecting candidate privacy is a challenge organisations must face when making data-driven hiring decisions in China.

Access to data

One of the major challenges of data-driven hiring in China is access to data. Many people in the country do not have access to or use the internet or digital platforms, which limits companies’ ability to gain data-driven recruitment insights. Moreover, even if they have access, much of the population may not use or trust such platforms enough to provide accurate information. This can lead to inaccurate recommendations and biassed decisions regarding recruitment and hiring.

Another challenge is the lack of up-to-date information on candidates that employers can use. Many companies require applicants to fill out paper forms that are often outdated and unreliable due to age or incorrect/inaccurate information provided by applicants themselves. This can lead to wasting time evaluating incomplete candidate profiles for job roles.

Data-driven hiring also poses a challenge for interviewing processes; many interviewers in China are not trained to use data correctly during interviews, making them unaware of potential biases and errors from any candidate selection process solely based on quantitative metrics and indicators. Therefore, there is a need for employers in China who are interested in using more data-driven approaches for recruitment efforts to understand how best utilise existing data sources efficiently before investing heavily into new sources.

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