6 Predictive Modelling Jobs

Location:Bangalore/Gurgaon/Hyderabad/Mumbai Must have skills: Must have skills:Data Scientist / Transformation Leader & at least 5 years in Telecom Analytics Good to have skills:GEN AI, Agentic AI, Job Summary : About Global Network Data & AI:- 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 About Comms & Media practice: Comms & Media (C&M) is one of the Industry Practices within Accentures 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 worlds 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. Roles & Responsibilities: 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. Professional & Technical Skills: Overall 10+ years of experience in Data Science & at least 5 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 Qualification Experience: Overall 10+ years of experience in Data Science & at least 5 years in Telecom Educational Qualification: Masters (MBA/MSc/MTech) from a Tier 1/Tier 2 and Engineering from Tier 1 school

Exp in SAS, SQL and large amounts of data US Stakeholder exp Exp of acquisition/account management credit risk models, transactional fraud models, marketing models, collections models, finance models, loss models, Loss forecasting (PD/LGD/EAD/CECL) Required Candidate profile SAS SQL Python Credit risk Credit Card Statistical Modelling Predictive Modelling

We will count on you to: Contribute to developing an inclusive work environment that respects and values differences of background, experience, and thought. Organize client data, check data for reasonability, load data into predictive models, run the models, share insights with senior colleagues, and compile coherent and compelling narratives to help clients understand their degree of risk. Perform basic calculations with client data to assess a range of risk exposures and predict outcomes for clients in support of reinsurance transaction process. Conduct research on industry/regulatory developments that affect loss liabilities to determine the impact on clients. Generating multiple exhibits, dashboards and decks leading to have impactful and insightful discussions with clients on their reinsurance strategy. Establish and maintain strong relationships with brokers/clients/reinsurers/colleagues, assist in promptly responding to client queries and concerns. Keep teams updated on industry-specific and specialty related trends that may affect reinsurance programs/calculations. Leverage our proprietary MetaRisk software suite and other internal tools to develop and optimize bespoke reinsurance transactions and evaluate their impact on our clients capital, growth, and volatility objectives. What you need to have: Bachelors or masters degree in a technical discipline such as Actuarial Science, Data Science, Engineering, Physics, Mathematics or Statistics. 2-4 years of work experience; completion of at least 2 actuarial exams preferred. Curious and proactive mindset: desire and ability to lead internal initiatives and research projects to completion. A collaborative, team-oriented mindset and effective interpersonal skills that is a positive and helpful presence in colleague and client interactions. Strong ability to be organized and detail oriented. Capacity to progress multiple projects at the same time. A desire and ability to grow beyond your current capabilities. Superior communication and presentation skills. Proficient in MS Excel with skills in other MS Office products. What makes you stand out: Familiarity with programming languages & visualization tools (i.e., R, Python, SQL, Alteryx, Power BI). Experience in a technical role at a reinsurance broker, market, or catastrophe model vendor. Prior experience in relevant re/insurance field. Understanding of the reinsurance industry and product lines.

This position would include the mentioned set of responsibilities but not limited to: Design and execute the company's data strategy and roadmap, including data governance, data quality, and data management to support the companys business goals and competitive positioning. Establish and enforce data governance principles, practices, policies, and standards to ensure data quality, integrity, and compliance. Define and oversee the data lifecycle management process, ensuring effective management of data from creation to archiving or deletion. Develop predictive models to identify potential credit risks, detect fraud, and optimize credit limit assignments. Collaborating with business stakeholders to identify data needs and drive data-driven decision-making Establish a strong data-driven approach to ensure decision-making across the organization Drive innovation through the use of artificial intelligence (AI), machine learning (ML), and predictive modelling. Leveraging modelling techniques to identify, analyze and present actionable data to drive business decisions Oversee the implementation of business intelligence (BI) and analytics initiatives to generate insights and enhance decision-making across various business functions, including risk management, marketing, and customer service Utilize data analytics to optimize pricing strategies, balance sheet management, and profitability projections. Implement strategies to enhance customer lifetime value (CLV) through data-driven decision-making. Develop and manage data analytics platforms and tools to provide actionable insights into customer behaviour, credit risk, and market trends in order to drive marketing campaigns, improve customer retention, and enhance overall customer experience. Leverage data to enhance customer segmentation, targeting, and personalization for more effective marketing and customer engagement. Lead the development, implementation, and maintenance of a comprehensive data governance framework across the organization. Oversee the collection, storage, and maintenance of data across the organization, ensuring accuracy and accessibility. Drive data innovation and analytics initiatives to uncover business insights and opportunities. Lead the data warehousing and data integration efforts to consolidate data from multiple sources (internal and external) for comprehensive analysis Mitigate risks related to data privacy and ensure ethical handling of customer data. Work closely with the Chief Information Security Officer (CISO) to ensure robust data security measures and protect against breaches or misuse. Work closely with Marketing and Product Development teams to use data insights to improve product offerings, pricing strategies, and customer acquisition efforts. Lead and manage data teams, including data analysts, data engineers, and data scientists Staying abreast of industry trends and emerging technologies to leverage data for competitive advantage Applicants should possess the following attributes Applicants should possess the following attributes Expertise in developing risk models for fraud detection and credit risk mitigation. Proficiency in customer segmentation, behavioural analysis, and targeted marketing strategies. Strategic Thinking: Ability to anticipate risks and align risk management strategies with the organization's long-term objectives. Leadership: Strong leadership skills to manage a diverse team and influence cross-functional stakeholders Analytical Expertise: High-level analytical capabilities to assess complex risk scenarios, conduct thorough analysis, and derive actionable insights. Regulatory Knowledge: Deep understanding of industry regulations and risk management best practices to ensure compliance and effective governance. Decision-Making: Strong, data-driven decision-making skills to manage crisis situations and recommend sound risk mitigation strategies. Proficiency in data analysis tools and techniques such as SQL, Python to generate insights and build financial models Strong understanding of data governance frameworks and experience with implementing data quality management practices that comply with RBI regulations, GDPR and other data privacy laws Business Intelligence & Reporting using BI tools for real time insights and decision support

Position Overview: This role leverages your extensive experience in Data Analytics and AI within a consulting framework to support growth of WNS analytics. It is ideal for a professional who excels in combining top-tier analytics skills with robust problem-solving and communication abilities to craft innovative solutions for customer, commercial, sales and marketing domains. These solutions typically integrate data, technology, and analytics to address strategic, tactical, and operational business challenges. This role demands creativity, drive, and a visionary approach. Key Responsibilities: Strategic Client Partnership and Solution Development: Collaborate with sales teams to forge and strengthen relationships with existing and potential clients in the data and analytics domain. Serve as the liaison between clients, sales, and analytics operations teams. Consult and upsell analytics services to existing clients, advancing them to more sophisticated offerings within the analytics value chain. Engage deeply with select clients to grow accounts and occasionally participate in discovery and delivery of Proof-of-Concept stages. Identify market opportunities, collaborate with business development teams to close sales, and contribute to the overall analytics strategy. Generate and communicate innovative ideas for new propositions, actively participating in go-to-market strategy development and lead generation tactics. Represent the company at trade shows, events, and industry associations. Expertise and Innovation: Act as the content knowledge expert in client interactions. Identify client requirements and design tailored analytics solutions and products. Collaborate with GTM proposition and Platform teams to influence the evolution of productized services with market insights. Business Travel: Engage in periodic domestic travel within India for collaboration and external meetings. Participate in international travel to the UK and US for client meetings as required. Skills and Experience: Technical Proficiency: Expertise in Predictive/Machine Learning Models, including Experiment Design, Causal Inference, Time Series, Marketing Mix Models, Bayesian Distributions, Regression, Decision Trees, Propensity models, SVMs. Strong numeracy, data literacy, and analytical skills. Programming experience in SQL, R, Python; knowledge of advanced MS Excel Working knowledge of visualization tools (e.g. Tableau, Power BI). Understanding of data management systems and modern cloud data infrastructure Ability to assimilate complex data and deliver clear presentations. Storytelling ability that combines Data Analytics and Business Logic. 10+ years of relevant experience. Client and Market Experience: Experience working with global clients and effective stakeholder management Extensive knowledge Applied Data Analytics, AI/ML techniques and BI Foundational understanding of Commercial Sales, Omnichannel Marketing programs and CRM analytics in sectors such as Manufacturing, Retail, Consumer and Tech, etc. Preferred but not essential: Masters Degree in Business. Communication and Collaboration: Effective and credible storyteller with the ability to map client challenges to internal capabilities and link conversations to business outcomes. Excellent written, verbal, and formal presentation skills for engaging diverse client audiences. Thrive in a collaborative team environment, defining issues/hypotheses, performing complex analysis, and preparing solution recommendations. Ability to think on your feet and engage with both business and analytical communities. Comfortable with ambiguity in a cross-functional environment. Willingness to work in a geographically distributed team structure in a fast-paced and challenging environment.

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.