Headquartered in Mumbai, India, WNS is a prominent global Business Process Management (BPM) and IT consulting company with 67 delivery centers and over 59,000 employees worldwide.
Combining extensive industry knowledge with technology, analytics, and process expertise, the company collaborates with clients across 10 industries to co-create digital-led transformational solutions. WNS is renowned for its strategic partnerships, delivering innovative practices and industry-specific technology and analytics-enabled solutions. The company’s services cover diverse sectors, characterised by a structured yet flexible approach, deep industry expertise, and a client-centric partnership model.
WNS Triange, the AI, analytics, data and research business unit, has successfully harnessed the power of data science to develop robust solutions that effectively address a myriad of business challenges faced by its clients.
Among these solutions are sophisticated applications such as an advanced claims processing system, a finely tuned inventory optimisation mechanism, and the implementation of a retail hyper-personalisation strategy.
Consisting of over 6,500 experts, WNS Triange serves as a partner for 200 global clients in more than 10 industries.
“The team is organised into three pillars: Triange Consult focuses on consulting and co-creating strategies for data, analytics, and AI; Triange NxT adopts an AI-led platform approach for scalable business value; and Triange CoE executes industry-specific analytics programs, transforming the value chain through domain expertise and strategic engagement models,” Akhilesh Ayer, EVP & Global Business Unit Head – WNS Triange, told AIM in an exclusive interaction last week.
WNS’s AI & Analytics Play
The data science workflow at WNS Triange follows a meticulously structured process that guides the team through various stages, including problem outlining, data collection, Exploratory Data Analysis (EDA), cleaning, pre-processing, feature engineering, model selection, training, evaluation, deployment, and continuous improvement. A pivotal element of this methodology is the proprietary AI-led platform, Triange NxT, equipped with Gen AI capabilities. This platform serves as a hub for domain and industry-specific models, expediting the delivery of impactful insights for clients.
“When it comes to claims processing, we deploy predictive analytics to conduct a thorough examination of data sourced from the First Notice of Loss (FNOL) and handler notes,” said Ayer. This approach allows for the evaluation of total loss probability, early settlement possibilities, and subrogation/recovery potential.
Simultaneously, its Marketing Mix Modeling (MMM) is employed to optimise resource allocation by quantifying the impact of marketing efforts on key performance indicators. Furthermore, the application of advanced analytics techniques aids in the detection of suspicious patterns in insurance claims for risk and fraud detection.
Ayer shared that the team also actively leverages generative AI across diverse sectors. In the insurance domain, it is employed to streamline claims subrogation by efficiently processing unstructured data, minimising bias, and expediting insights for recovery.
Similarly, in healthcare, it empowers Medical Science Liaisons (MSLs) by summarising documents and integrating engagement data for more impactful sales pitches. Generative AI’s versatility is further demonstrated in customer service interactions, where it adeptly handles natural language queries, ensuring quicker responses and retrieval efficiency.
The combination of LLM foundation models from hyperscalers like AWS with WNS Triange’s proprietary ML models enables the delivery of tailored solutions that cater to various functional domains and industries. Where necessary, WNS Triange employs its AI, ML and domain capability to fine-tune existing foundation models for specific results, ensuring a nuanced and effective approach to problem-solving.
Tech Stack
In its AI model development, the team utilises vector databases and deep learning libraries such as Keras, PyTorch, and TensorFlow. Knowledge graphs are integrated, and MLOps and XAI frameworks are implemented for enterprise-grade solutions.
“Our tech stack includes Python, R, Spark, Azure, machine learning libraries, AWS, GCP, and GIT, reflecting our commitment to using diverse tools and platforms based on solution requirements and client preferences,” said Ayer.
Even when it comes to using transformer technology, particularly language models like Google’s BERT for tasks such as sentiment analytics and entity extraction, its current approach involves a variety of language models, including GPT variants (davinci-003, davinci-codex, text-embedding-ada-002), T5, BART, LLaMA, and Stable Diffusion.
“We adopt a hybrid model approach, integrating Large Language Models (LLMs) from major hyperscalers like OpenAI, Titan, PaLM2, and LLaMA2, enhancing both operational efficiency and functionality,” he commented.
Hiring Process
WNS Triange recruits data science talent from leading engineering colleges, initiating the process with a written test evaluating applied mathematics, statistics, logical reasoning, and programming skills. Subsequent stages include a coding assessment, a data science case study, and final interviews with key stakeholders.
“Joining our data science team offers candidates a dynamic and challenging environment with ample opportunities for skill development. And while engaging in diverse projects across various industries, individuals can expect exposure to both structured and unstructured data,” said Ayer.
The company fosters a collaborative atmosphere, allowing professionals to work alongside colleagues with diverse backgrounds and expertise. Emphasis is placed on leveraging cutting-edge technologies and providing hands-on experience with state-of-the-art tools and frameworks in data science.
WNS Triange values participation in impactful projects contributing to the company’s success, offering access to mentorship programs and support from experienced team members, ensuring a positive and productive work experience.
Mistakes to Avoid
Candidates are encouraged to not only showcase technical prowess but also articulate the business impact of their work, demonstrating its real-world relevance and contribution to business goals.
Ayer emphasised, “Successful data scientists must not only be technically adept but also skilled storytellers to present their findings in a compelling manner, as overlooking this aspect can lead to less engaging presentations of their work”
He added that candidates sometimes focus solely on technical details without articulating the business impact of their work, missing the opportunity to demonstrate how their analyses and models solve real-world problems and contribute to business goals.
Work Culture
Recognised by TIME MAGAZINE for being one of the best companies to work in, WNS has built a work culture centered on co-creation, innovation, and a people-centric approach, emphasising diversity, equity, and inclusivity, prioritising a respectful workplace culture and extending its commitment to community care through targeted programs by the WNS Cares Foundation.
“Our focus on ethics, integrity, and compliance ensures a safe ecosystem for all stakeholders, delivering value to clients through comprehensive business transformation,” said Ayer.
In terms of employee perks, it offers various services and benefits, including transportation, cafeterias, medical and recreational facilities, flexibility in work hours, health insurance, and parental leave.
“Differentiating ourselves in the data science space, we cultivate a work ecosystem that fosters innovation, continuous learning, and belongingness for the data science team. Our initiatives include engagement tools, industry-specific training programs, customised technology-driven solutions, and a learning experience platform hosting a wealth of content for self-paced learning,” he added.
Why Should You Join WNS?
“At WNS, we believe in the transformative power of data, where individuals play a key role in shaping our organisation by directly influencing business strategy and decision-making. Recognising the significant impact of data science, we invite individuals to join our collaborative and diverse team that encourages creativity and values innovative ideas. In this dynamic environment, we prioritise knowledge sharing, continuous learning, and professional growth,” concluded Ayer.
Find more information about job opportunities at WNS here.
