Entity :- Accenture Strategy & Consulting Team :- Strategy & Consulting Global Network Practice :- Data & AI - CMT Title :- Consultant Level 9 Job location :- Bangalore/Gurgaon/Hyderabad Accenture Strategy & Consulting Global Network - Data & AI practice help our clients grow their business in entirely new ways. Analytics enables our clients to achieve high performance through insights from data - insights that inform better decisions and strengthen customer relationships. From strategy to execution, Accenture works with organizations to develop analytic capabilities - from accessing and reporting on data to predictive modelling - to outperform the competition As part of our Data & AI practice, you will join a worldwide network of over 20,000 smart and driven colleagues experienced in leading AI/ML/Statistical tools, methods and applications. From data to analytics and insights to actions, our forward-thinking consultants provide analytically informed, issue-based insights at scale to help our clients improve outcomes and achieve high performance. About Comms & Media practice within Strategy & Consulting: Comms & Media (C&M) is one of the Industry Practices within Accenture's S&C Global Network team. It focuses in serving clients across specific Industries Communications, Media & Entertainment. Communications Focuses primarily on industries related with telecommunications and information & communication technology (ICT). This team serves most of the world's leading wireline, wireless, cable and satellite communications and service providers Media & Entertainment Focuses on industries like broadcast, entertainment, print and publishing Globally, Accenture Comms & Media practice works to develop value growth strategies for its clients and infuse AI & GenAI to help deliver top their business imperatives i.e., revenue growth & cost reduction. From multi-year Data & AI transformation projects to shorter more agile engagements, we have a rapidly expanding portfolio of hyper-growth clients and an increasing footprint with next-gen solutions and industry practices. Responsibilities/Authorities A Telco domain experienced and data science consultant is responsible to help the clients with designing & delivering AI solutions. He/she should be strong in Telco domain, AI fundamentals and should have good hands-on experience working with the following: Ability to work with large data sets and present conclusions to key stakeholders; Data management using SQL. Propose solutions to the client based on gap analysis for the existing Telco platforms that can generate long term & sustainable value to the client. Gather business requirements from client stakeholders via interactions like interviews and workshops with all stakeholders Track down and read all previous information on the problem or issue in question. Explore obvious and known avenues thoroughly. Ask a series of probing questions to get to the root of a problem. Ability to understand the as-is process; understand issues with the processes which can be resolved either through Data & AI or process solutions and design detail level to-be state Understand customer needs and identify/translate them to business requirements (business requirement definition), business process flows and functional requirements and be able to inform the best approach to the problem. Adopt a clear and systematic approach to complex issues (i.e. A leads to B leads to C). Analyze relationships between several parts of a problem or situation. Anticipate obstacles and identify a critical path for a project. Independently able to deliver products and services that empower clients to implement effective solutions. Makes specific changes and improvements to processes or own work to achieve more. Work with other team members and make deliberate efforts to keep others up to date. Establish a consistent and collaborative presence with clients and act as the primary point of contact for assigned clients; escalate, track, and solve client issues. Partner with clients to understand end clients' business goals, marketing objectives, and competitive constraints. Storytelling Crunch the data & numbers to craft a story to be presented to senior client stakeholders. Should be able to travel or relocate to Japan as per business requirement. Qualifications JOB REQUIREMENTS Overall Experience Overall 5+ years of experience in Data Science & at least 3 years in Telecom Analytics Masters (MBA/MSc/MTech) from a Tier 1/Tier 2 and Engineering from Tier 1 school Demonstrated experience in solving real-world data problems through Data & AI Direct onsite experience (i.e., experience of facing client inside client offices in India or abroad) is mandatory. Please note we are looking for client facing roles. Proficiency with data mining, mathematics, and statistical analysis Advanced pattern recognition and predictive modeling experience; knowledge of Advanced analytical fields in text mining, Image recognition, video analytics, IoT etc. Execution level understanding of econometric/statistical modeling packages Traditional techniques like Linear/logistic regression, multivariate statistical analysis, time series techniques, fixed/Random effect modelling. Machine learning techniques like - Random Forest, Gradient Boosting, XG boost, decision trees, clustering etc. Knowledge of Deep learning modeling techniques like RNN, CNN etc. Experience using digital & statistical modeling software (one or more) Python, R, PySpark, SQL, BigQuery, Vertex AI Proficient in Excel, MS word, Power point, and corporate soft skills Knowledge of Dashboard creation platforms Excel, tableau, Power BI etc. Excellent written and oral communication skills with ability to clearly communicate ideas and results to non-technical stakeholders. Strong analytical, problem-solving skills and good communication skills Self-Starter with ability to work independently across multiple projects and set priorities Strong team player Proactive and solution oriented, able to guide junior team members. Execution knowledge of optimization techniques is a good-to-have Exact optimization Linear, Non-linear optimization techniques Evolutionary optimization Both population and search-based algorithms Cloud platform Certification, experience in Computer Vision are good-to-haves

• Demonstrated understanding and experience in applying traditional statistical, traditional machine learning, capacity forecasting , timeseries forecasting deep learning, to address business problems • Data management and governance • Doing independent research, analyze, and present data as assigned • Managing the learning and development of new team members • Recruitment and retention management • Identify and participate in continuous improvement initiatives • Ensure compliance with Data Privacy and Protection Guidelines • Participate in business development activities • Experience in insurance preferred but not mandatory.

Salary : 20 to 35 LPA Exp: 4 to 8 years Location :Noida/Gurugram/Bangalore Notice: Immediate to 30 days..!! Roles & responsibilities: 4+ years exp on Python , ML and Banking model development Interact with the client to understand their requirements and communicate / brainstorm solutions, model Development: Design, build, and implement credit risk model. Contribute to how analytical approach is structured for specification of analysis Contribute insights from conclusions of analysis that integrate with initial hypothesis and business objective. Independently address complex problems 3+ years exp on ML/Python (predictive modelling) . Design, implement, test, deploy and maintain innovative data and machine learning solutions to accelerate our business. Create experiments and prototype implementations of new learning algorithms and prediction techniques Collaborate with product managers, and stockholders to design and implement software solutions for science problems Use machine learning best practices to ensure a high standard of quality for all of the team deliverables Has experience working on unstructured data ( text ): Text cleaning, TFIDF, text vectorization Hands-on experience with IFRS 9 models and regulations. Data Analysis: Analyze large datasets to identify trends and risk factors, ensuring data quality and integrity. Statistical Analysis: Utilize advanced statistical methods to build robust models, leveraging expertise in R programming. Collaboration: Work closely with data scientists, business analysts, and other stakeholders to align models with business needs. Continuous Improvement: Stay updated with the latest methodologies and tools in credit risk modeling and R programming.

Job Information Date Opened 02/28/2025 Job Type Permanent RSD NO 10502 Industry IT Services Min Experience 4 years Max Experience 8 years City Chennai State/Province Tamil Nadu Country India Zip/Postal Code 600001 Job Description Role: Senior Data Scientist with expertise in Marketing and Product analytics across domains but especially Retail, Consumer Goods & Products and E-commerce Skill & Experience • Hands on experience with Exploratory Data Analysis and Data Wrangling using Pandas, Polars, NumPy, DuckDB • Applied knowledge of statistical concepts like Hypothesis Testing, AB Testing, p-values and Normal, Binomial, Beta, Gamma, Exponential and Poisson distributions • Applied knowledge of working on data science models like Marketing Mix models, RFM (Recency Frequency Monetary) Analysis, Price Elasticity, Dynamic Pricing, Campaign Optimization etc. • Working knowledge of implementation and maths behind data science algorithms such as Linear & Logistic Regression and their variants like Lasso and Ridge • Should have good understanding of data science algorithms like Random Forest and Xgboost • Understanding of Neural Networks and Deep Learning is a plus not a requirement • Understanding of cloud tools on AWS, Azure would be a great plus • Understanding of Python API frameworks would be a great plus • Preference would be given to a LLM/AI savvy candidate who uses it make their work more effective • Should be able to write good SQL code to extract and analyse data • Should be comfortable using Excel • Should have above average critical thinking and written+oral communication skills • # of years of experience is not a strict bar for the right candidate, but try to look at 5+ years At Indium diversity, equity, and inclusion (DEI) are the cornerstones of our values. We champion DEI through a dedicated council, expert sessions, and tailored training programs, ensuring an inclusive workplace for all. Our initiatives, including the WE@IN women empowerment program and our DEI calendar, foster a culture of respect and belonging. Recognized with the Human Capital Award, we are committed to creating an environment where every individual thrives. Join us in building a workplace that values diversity and drives innovation.

Job Description Purpose of the role To design, develop, implement, and support mathematical, statistical, and machine learning models and analytics used in business decision-making Accountabilities Design analytics and modelling solutions to complex business problems using domain expertise. Collaboration with technology to specify any dependencies required for analytical solutions, such as data, development environments and tools. Development of high performing, comprehensively documented analytics and modelling solutions, demonstrating their efficacy to business users and independent validation teams. Implementation of analytics and models in accurate, stable, well-tested software and work with technology to operationalise them. Provision of ongoing support for the continued effectiveness of analytics and modelling solutions to users. Demonstrate conformance to all Barclays Enterprise Risk Management Policies, particularly Model Risk Policy. Ensure all development activities are undertaken within the defined control environment. Analyst Expectations To perform prescribed activities in a timely manner and to a high standard consistently driving continuous improvement. Requires in-depth technical knowledge and experience in their assigned area of expertise Thorough understanding of the underlying principles and concepts within the area of expertise They lead and supervise a team, guiding and supporting professional development, allocating work requirements and coordinating team resources. If the position has leadership responsibilities, People Leaders are expected to demonstrate a clear set of leadership behaviours to create an environment for colleagues to thrive and deliver to a consistently excellent standard. The four LEAD behaviours are: L Listen and be authentic, E – Energise and inspire, A – Align across the enterprise, D – Develop others. OR for an individual contributor, they develop technical expertise in work area, acting as an advisor where appropriate. Will have an impact on the work of related teams within the area. Partner with other functions and business areas. Takes responsibility for end results of a team’s operational processing and activities. Escalate breaches of policies / procedure appropriately. Take responsibility for embedding new policies/ procedures adopted due to risk mitigation. Advise and influence decision making within own area of expertise. Take ownership for managing risk and strengthening controls in relation to the work you own or contribute to. Deliver your work and areas of responsibility in line with relevant rules, regulation and codes of conduct. Maintain and continually build an understanding of how own sub-function integrates with function, alongside knowledge of the organisations products, services and processes within the function. Demonstrate understanding of how areas coordinate and contribute to the achievement of the objectives of the organisation sub-function. Make evaluative judgements based on the analysis of factual information, paying attention to detail. Resolve problems by identifying and selecting solutions through the application of acquired technical experience and will be guided by precedents. Guide and persuade team members and communicate complex / sensitive information. Act as contact point for stakeholders outside of the immediate function, while building a network of contacts outside team and external to the organisation. All colleagues will be expected to demonstrate the Barclays Values of Respect, Integrity, Service, Excellence and Stewardship – our moral compass, helping us do what we believe is right. They will also be expected to demonstrate the Barclays Mindset – to Empower, Challenge and Drive – the operating manual for how we behave. Additional Job Description Join us as a "Data Scientist" in Group Control Quantitative Analytics team at Barclays, where you'll spearhead the evolution of our digital landscape, driving innovation and excellence. You'll harness cutting-edge technology to revolutionize our digital offerings, ensuring unapparelled customer experiences. Group Control Quantitative Analytics (GC QA) is a global organization of highly specialized data scientists working on Machine Learning model development and model management including governance and monitoring. GC QA is led by Lee Gregory, who is Chief Data and Analytics Officer (CDAO) in Group Control. GC QA is responsible for developing and managing machine learning models (including governance and regular model monitoring ) and providing analytical support across different areas including Fraud, Financial Crime, Controls, Security etc. within Barclays. The Data Scientist" position provides project specific leadership in building targeting solutions that integrate effectively into existing systems and processes while delivering strong and consistent performance. Working with GC CDAO team, the Quantitative Analytics Data Scientist role provides expertise in project design, predictive model development, validation, monitoring, tracking and implementation. To be successful as a "Data Scientist" in Group Control Quantitative Analytics team, you should have experience with: Coding using Python. Machine Learning algorithms. SQL Distributed computing using Spark/PySpark. Predictive Model development. Model lifecycle and model management including monitoring. DevOps tools like Git/Bitbucket etc. Project management using JIRA. Some other highly valued skills may include: DevOps tools Teamcity, Jenkins etc. Knowledge in Fraud and Financial Crime domain. Knowledge of GenAI tools and working. DataBricks You may be assessed on the key critical skills relevant for success in role, such as risk and controls, change and transformation, business acumen strategic thinking and digital and technology, as well as job-specific technical skills. Location: Noida.

Salary : 15 to 35 LPA Exp: 2 to 6 years Location :Noida/Gurugram/Bangalore Notice: Immediate to 30 days..!! Roles & responsibilities: 2+ years exp on Python , ML and Banking model development Interact with the client to understand their requirements and communicate / brainstorm solutions, model Development: Design, build, and implement credit risk model. Contribute to how analytical approach is structured for specification of analysis Contribute insights from conclusions of analysis that integrate with initial hypothesis and business objective. Independently address complex problems 3+ years exp on ML/Python (predictive modelling) . Design, implement, test, deploy and maintain innovative data and machine learning solutions to accelerate our business. Create experiments and prototype implementations of new learning algorithms and prediction techniques Collaborate with product managers, and stockholders to design and implement software solutions for science problems Use machine learning best practices to ensure a high standard of quality for all of the team deliverables Has experience working on unstructured data ( text ): Text cleaning, TFIDF, text vectorization Hands-on experience with IFRS 9 models and regulations. Data Analysis: Analyze large datasets to identify trends and risk factors, ensuring data quality and integrity. Statistical Analysis: Utilize advanced statistical methods to build robust models, leveraging expertise in R programming. Collaboration: Work closely with data scientists, business analysts, and other stakeholders to align models with business needs. Continuous Improvement: Stay updated with the latest methodologies and tools in credit risk modeling and R programming.

Role & responsibilities : Key Result Areas 1. Implementation of Actionable Analytics Program in close coordination with the functional stakeholders Getting sponsorship from leadership and senior management on specific analytics initiatives and report progress on a regular basis Cross-functional coordination for driving business intervention with various teams incl. IT. Digital, Marketing and respective stakeholders. Drive Establish processes and manage development of infrastructure (e.g. IT, Marketing) to support analytics program Validate statistical models, implementation and actionable and improve efficacy and efficiency of analytics program 2. Revenue enhancement initiatives Increasing conversion through Better customer segmentation, targeting and Response modelling and campaign design New target opportunities including social listening Increasing cross-sell / upsell through Marketing (Upsell/ Cross-sell) of health insurance to Distributors customers to increase conversion rates Wellness & lifestyle partner up-sell/ cross-sell Cross-sell Wellness products to existing health insurance customers Increase Customer Retention Maximize renewal collection and reducing lapse rate 3. Cost and Claims optimization initiatives Cost reduction incl. optimization of campaigns Risk reduction including Claims adjudication and UW and claims/loss fraud investigation Optimization of model on a frequent basis 4. Increasing customer engagement loyalty initiatives Designing strategies to get low engagement clients to engage more. Maintain Planned spends across partners 5. Building data marts and models for Revenue enhancement and claims /cost initiatives Increasing cross-sell / upsell and Increase Customer Retention Risk reduction including Claims adjudication and UW and claims/loss fraud investigation Health risk reduction analytics 6. Resource Management and Develop individual and team competence to achieve overall effectiveness . Ensure elaborate functional knowledge sharing and extensive training to have a well-motivated and effective team who can provide high quality support and innovative solutions.

2+ yrs exp in AI/ML, implementing & optimizing solutions using Deep Learning, NLP, Tensorflow, Keras, XGBoost, etc. Expertise in closed/open source LLMs (GPT 3.5/4/4 Turbo, LLAMA2, Falcon). Expert in Python. Deployed AI/ML as services on Cloud/K8s. Required Candidate profile Familiarity with development methodologies and writing Python unit tests. Preferred experience includes working with Open Source LLMs such as LLAMA2 and Falcon, with emphasis on fine-tuning.

2+ yrs exp in AI/ML, implementing & optimizing solutions using Deep Learning, NLP, Tensorflow, Keras, XGBoost, etc. Expertise in closed/open source LLMs (GPT 3.5/4/4 Turbo, LLAMA2, Falcon). Expert in Python. Deployed AI/ML as services on Cloud/K8s. Required Candidate profile Familiarity with development methodologies and writing Python unit tests. Preferred experience includes working with Open Source LLMs such as LLAMA2 and Falcon, with emphasis on fine-tuning.

The Data Scientist role requires a highly analytical individual proficient in Python programming, database management, and data science methodologies. You'll focus on extracting insights from data, developing and implementing machine learning models, managing big data infrastructure, and supporting AI-driven product development. Key Responsibilities:Data Collection and Cleansing:Collect and cleanse data from diverse sources to ensure high-quality datasets for decision-making. Data Exploration and Visualization:Explore and visualize data using advanced techniques to uncover insights and trends. Statistical Analysis:Apply statistical and mathematical techniques to provide robust analytical foundations for predictive modeling. Machine Learning and Deep Learning:Develop and implement machine learning and deep learning models to address business challenges. ML-Ops / AI-Ops:Demonstrate expertise in ML-Ops / AI-Ops practices to ensure efficient model deployment and management. Big Data Management:Manage big data infrastructure and execute data engineering tasks for efficient data processing. Version Control and Collaboration:Utilize version control systems like Git for maintaining codebase integrity and fostering collaboration. AI-Driven Product Development:Design, create, and support AI-driven products to deliver impactful solutions aligned with user needs and business objectives. Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise 5+ years of expertise in Statistical Modeling and Machine Learning:Demonstrable deep understanding of statistics, machine learning, deep learning, neural networks, and NLP/NLU. Strong programming skills in Python or R for data manipulation, analysis, and modeling. Proficiency in machine learning frameworks and libraries (e.g., scikit-learn, TensorFlow, Keras, XGBoost, PyTorch). Familiarity with cloud platforms (e.g., AWS, GCP, Azure) and big data tools (e.g., Spark, Hadoop). Experience with SQL and working with large, complex datasets. Ability to interpret complex data patterns and translate them into actionable insights. Preferred technical and professional experience Knowledge of optimization techniques and algorithms for large-scale data problems. Familiarity with MLOps principles and practices. Familiarity with natural language processing (NLP), computer vision techniques, LLMs.