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Connecticut-based Samsung subsidiary, HARMAN, is a global leader in audio, automotive, and connected technologies, offering a range of innovative and high-quality products and solutions to customers around the world. Founded in 1980 by Sidney Harman and Bernard Kardon, the company has grown to become a prominent player in the industry, with a strong reputation for delivering exceptional sound experiences, intelligent automation solutions, and seamless connectivity across devices and platforms.
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Harman’s portfolio includes a wide range of products and services, including audio and video systems, car audio, connected car solutions, professional audio and lighting equipment, and more. Harman is the parent company to a variety of brands like JBL, Harman Kardon, AKG, Mark Levinson, and Infinity Systems.
HARMAN empowers global enterprises with cutting-edge solutions that harness the immense potential of cloud computing, applied AI, data, IoT, advanced analytics, metaverse, quantum computing, cybersecurity, and 5G. The team uses data science to address a wide range of business issues in sectors like healthcare, communications, industry, retail, software, and hospitality.
Analytics India Magazine got in touch with Dr Jai Ganesh, chief product officer of HARMAN to know how the company implements AI in their daily lives and also their hiring process for talent and work culture. He is an alumnus of IIM-Bangalore and the University of Oxford. “We believe technology has the power to transform the world for the better and we build solutions that address some of the most pressing challenges facing enterprises and society,” said Ganesh.
Inside HARMAN’s Data Science Team
The AI, data and analytics team at HARMAN is 2500-strong. There is a centralised data science team as part of the chief product officer’s organisation, which is responsible for building AI-ML accelerators such as MLOps framework, building AI-ML based features and functionalities in products as well as creating proof of value demos. Each of their six key verticals consisting of healthcare, communications, industrial, retail, software, and hospitality has its own data science teams who work on client-facing projects.
“HARMAN’s data science team has made significant contributions by incorporating machine learning and deep learning models into a range of applications, such as predictive analytics, computer vision, NLP, and graph analytics,” said Ganesh. These cutting-edge models enable HARMAN to enhance the customer experience and engagement by providing AI/ML-driven insights gleaned from various data sources.
The data science team of HARMAN leverages both open source as well as commercial tools, applications and frameworks such as Python, TensorFlow, PyTorch, AWS, Azure, or Google Cloud Platform, Java, C++, Git, Jenkins, Docker, Kubernetes, R, Jupyter, SAS, MongoDB, Spark, Kafka, MySQL, RStudio, KNIME, RapidMiner, H2O etc.
These models have diverse applications, ranging from predicting hospital readmissions with an accuracy rate of 93%, using over 50 inpatient data variables to identify risk factors, to powering conversational AI, recommendation engines, optimisation, and fraud-risk models.
HARMAN has further cemented its position as an industry leader by unveiling its ‘Intelligent Healthcare Platform’ at CES 2023, which harnesses the power of AI and machine learning to provide actionable insights that improve customer engagement through predictive analytics. When it comes to customisation, HARMAN has also implemented AR and VR on JBL’s customisation page.
Hiring Process
From freshers to senior positions, the company hires for different laterals.
The interview process for hiring data science roles includes at least five rounds where the candidates are assessed on their conceptual, technical, problem-solving, team-playing, coding, and learning strength.
One of the most common mistakes candidates make is they don’t research well about the company before applying and focus only on technical skills.
Expectations
HARMAN expects potential employees to have a strong foundation in programming languages such as Python, R, or Java. They should also be proficient in coding, debugging, and testing. It is critical to have a solid understanding of linear algebra, calculus, probability theory, and statistics to comprehend the underlying concepts of machine learning algorithms.
Familiarity with ML algorithms such as supervised learning, unsupervised learning, reinforcement learning, and deep learning is essential. Experience in data cleaning, transformation, feature engineering, and normalisation is also important to prepare data for machine learning algorithms. Additionally, good communication skills, problem-solving skills, and a willingness to learn new concepts, algorithms, and technologies are required to excel in this constantly evolving field.
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At the same time, employees can expect to have the freedom to think innovatively and work with a team of ambitious individuals from around the world and actively grasp the opportunities for learning, growth, and personal development.
Work Culture
“HARMAN’s people are the biggest distinguishing factor that set the company apart from its competitors,” said Ganesh.
HARMAN’s culture prioritises support, innovation, and excitement, and their diversity fosters innovative thinking. The company makes sure that you balance your personal and professional life well. Employees collaborate from different backgrounds to find innovative solutions and achieve technical successes. It offers employees a place to grow and feel like family.
Besides flexible working hours, hybrid office, and health insurance, HARMAN has other special perks for its employees, including the ReInventHers initiative, which focuses on aiding women who are resuming their careers after a break, and the AMIGO Maternity Engagement Program, which provides support to women employees during and after pregnancy.
So, people who are comfortable with numbers who aim to make it big, maybe the right fit for HARMAN.
Click here to apply.
