3 Arimax Jobs

Company Description WNS (Holdings) Limited (NYSE: WNS), is a leading Business Process Management (BPM) company. We combine our deep industry knowledge with technology and analytics expertise to co-create innovative, digital-led transformational solutions with clients across 10 industries. We enable businesses in Travel, Insurance, Banking and Financial Services, Manufacturing, Retail and Consumer Packaged Goods, Shipping and Logistics, Healthcare, and Utilities to re-imagine their digital future and transform their outcomes with operational excellence.We deliver an entire spectrum of BPM services in finance and accounting, procurement, customer interaction services and human resources leveraging collaborative models that are tailored to address the unique business challenges of each client. We co-create and execute the future vision of 400+ clients with the help of our 44,000+ employees. Job Description Job Overview: Responsible for leading data science initiatives, developing advanced analytics models and ensuring successful execution of data-driven projects for clients in the retail. Will work closely with key client stakeholders to understand their business challenges and leverage data science to deliver actionable insights that drive business growth and efficiency.Lead the design, development and implementation of advanced analytics models. Including predictive and prescriptive models for retail clients.Should be able to convert mathematical/ statistics-based research into sustainable data science solutionsCandidate should be able to think from first principles to define & evangelize solutions for any client business problemLeverage deep knowledge of the retail to develop data-driven solutions that address industry-specific challenges. Apply AI/ML statistical methods to solve complex business problems and determine new opportunities for clients.Ensure project delivery of high-quality, actionable insights that drive business decisions and outcomes.Ensure end-to-end lifecycle (scoping to Delivery) of data science projects.Collaborate with cross-functional teams to ensure seamless project execution.Manage timelines, resources, and deliverables to meet client expectations and project goals.Drive innovation by exploring new data science techniques, tools, and technologies that can enhance the value delivered to clients.Strong hands-on experience with data science tools and technologies (e.g., Python, R, SQL, machine learning frameworks).Hand-on experience with a range of data science models including regression, classification, clustering, decision tree, random forest, support vector machine, nave Bayes, GBM, XGBoost, multiple linear regression, logistic regression, and ARIMA/ARIMAX.Should be competent in Python (Pandas, NumPy, scikit-learn etc.), possess high levels of analytical skills and have experience in the creation and/or evaluation of predictive models.Preferred experience in areas such as time series analysis, market mix modelling, attribution modelling, churn modelling, market basket analysis, etcGood communication and project management skills. Should be able to communicate effectively to a wide range of audiences, both technical and business. Adept in creating Presentations, reports etc to present theanalysis findings to key client stakeholders. Strong team management skills with a passion for mentoring and developing talent. Qualifications BTech/Masters in Statistics/Mathematics/Economics/Econometrics from Tier 1-2 institutions Or BE/B-Tech, MCA or MBA7-10 years of hands-on relevant experience in delivering Data Science/Analytics projects. Show more Show less

The Senior Data Science Lead is a pivotal role responsible for driving the research, development, and deployment of semi-autonomous AI agents to solve complex enterprise challenges. This role involves hands-on experience with LangGraph, leading initiatives to build multi-agent AI systems that operate with greater autonomy, adaptability, and decision-making capabilities. The ideal candidate will have deep expertise in LLM orchestration, knowledge graphs, reinforcement learning (RLHF/RLAIF), and real-world AI applications. As a leader in this space, they will be responsible for designing, scaling, and optimizing agentic AI workflows, ensuring alignment with business objectives while pushing the boundaries of next-gen AI automation. Key Responsibilities: 1. Architecting & Scaling Agentic AI Solutions: - Design and develop multi-agent AI systems using LangGraph for workflow automation, complex decision-making, and autonomous problem-solving. - Build memory-augmented, context-aware AI agents capable of planning, reasoning, and executing tasks across multiple domains. - Define and implement scalable architectures for LLM-powered agents that seamlessly integrate with enterprise applications. 2. Hands-On Development & Optimization: - Develop and optimize agent orchestration workflows using LangGraph, ensuring high performance, modularity, and scalability. - Implement knowledge graphs, vector databases (Pinecone, Weaviate, FAISS), and retrieval-augmented generation (RAG) techniques for enhanced agent reasoning. - Apply reinforcement learning (RLHF/RLAIF) methodologies to fine-tune AI agents for improved decision-making. 3. Driving AI Innovation & Research: - Lead cutting-edge AI research in Agentic AI, LangGraph, LLM Orchestration, and Self-improving AI Agents. - Stay ahead of advancements in multi-agent systems, AI planning, and goal-directed behavior, applying best practices to enterprise AI solutions. - Prototype and experiment with self-learning AI agents, enabling autonomous adaptation based on real-time feedback loops. 4. AI Strategy & Business Impact: - Translate Agentic AI capabilities into enterprise solutions, driving automation, operational efficiency, and cost savings. - Lead Agentic AI proof-of-concept (PoC) projects that demonstrate tangible business impact and scale successful prototypes into production. 5. Mentorship & Capability Building: - Lead and mentor a team of AI Engineers and Data Scientists, fostering deep technical expertise in LangGraph and multi-agent architectures. - Establish best practices for model evaluation, responsible AI, and real-world deployment of autonomous AI agents.,

At PwC, the focus in data and analytics is on leveraging data to drive insights and make informed business decisions. Utilizing advanced analytics techniques to help clients optimize their operations and achieve strategic goals is key. In data analysis at PwC, the emphasis is on utilizing advanced analytical techniques to extract insights from large datasets and drive data-driven decision-making. Skills in data manipulation, visualization, and statistical modeling play a crucial role in supporting clients in solving complex business problems. Candidates with 4+ years of hands-on experience are sought for the position of Senior Associate in supply chain analytics. Successful candidates should possess proven expertise in supply chain analytics across domains such as demand forecasting, inventory optimization, logistics, segmentation, and network design. Additionally, hands-on experience working on optimization methods like linear programming, mixed integer programming, and scheduling optimization is required. Proficiency in forecasting techniques and machine learning techniques, along with a strong command of statistical modeling, testing, and inference, is essential. Familiarity with GCP tools like BigQuery, Vertex AI, Dataflow, and Looker is also necessary. Required skills include building data pipelines and models for forecasting, optimization, and scenario planning, strong SQL and Python programming skills, experience deploying models in a GCP environment, and knowledge of orchestration tools like Cloud Composer (Airflow). Nice-to-have skills consist of familiarity with MLOps, containerization (Docker, Kubernetes), and orchestration tools, as well as strong communication and stakeholder engagement skills at the executive level. The roles and responsibilities of the Senior Associate involve assisting analytics projects within the supply chain domain, driving design, development, and delivery of data science solutions. They are expected to interact with and advise consultants/clients as subject matter experts, conduct analysis using advanced analytics tools, and implement quality control measures for deliverable integrity. Validating analysis outcomes, making presentations, and contributing to knowledge and firm building activities are also part of the role. The ideal candidate should hold a degree in BE / B.Tech / MCA / M.Sc / M.E / M.Tech / Masters Degree / MBA from a reputed institute.,