- Job description
Accenture Digital, comprised of Accenture Analytics, Accenture Interactive and Accenture Mobility, offers a comprehensive portfolio of business and technology services across digital marketing, mobility and analytics. From developing digital strategies to implementing digital technologies and running digital processes on their behalf, Accenture Digital helps clients leverage connected and mobile devices; extract insights from data using analytics; and enrich end-customer experiences and interactions, delivering tangible results from the virtual world and driving growth. To learn more about Accenture Digital, follow us @AccentureDigi and visit www.accenture.com/digital.
Accenture Analytics, part of Accenture Digital, helps clients to use analytics and artificial intelligence to drive actionable insights, at scale. Accenture Analytics applies sophisticated algorithms, data engineering and visualization to extract business insights and help clients turn those insights into actions that drive tangible outcomes – to improve their performance and disrupt their markets. With deep industry and technical experience, Accenture Analytics provides services and solutions that include, but are not limited to: analytics-as-a-service through the Accenture Insights Platform, continuous intelligent security, machine learning, and IoT Analytics. For more information, follow us @ISpeakAnalytics and visit www.accenture.com/analytics.
Provide consulting support to solve for business problems in the area of customer analytics for the CMT / Telecom domain through Predictive analytics based solutions and perform quantitative ad-hoc analyses to create valuable insights from data.
• Proficiency in two or more of analytical tools such as SAS product suite (Base Stats, E-miner, SAS EGRC), SPSS, SQL, KXEN and any other statistical tools such as R, MATLAB etc. (SAS/R are must)
• Good knowledge of one of more programming language such as Python, Java, C++ is a plus
• Advanced Excel including VBA and PowerPoint skills
• Willingness to be flexible and work on traditional techniques as per business need
• Consulting skills and project management experience is preferred
• Excellent communication and interpersonal skills as well as collaborative, team player
• Ability to tie analytic solutions to business/industry value and outcomes
• Autonomous, self-starter with a passion for analytics and problem solving
• Utilize state of the art Machine learning and optimization algorithms for targeting customers to increase profitability, acquire new customers and increase retention. Propose and apply new algorithms for the same
• Demonstrated analytical expertise, including the ability to synthesize complex data, effectively manage complex analyses, technical understanding of system capabilities and constraints
• Develop methodologies to support Customer Analytical project execution for CMT / Telecom clients
• Develop predictive analytics based solutions for
o Customer Segmentation
o Statistical Models across customer Lifecycle
o Attrition / Cross-Sell / Upsell Propensity Models
o Customer Lifetime Value
o Pricing Analytics
o Web Analytics
• Apply appropriate techniques, such as exploratory data analysis, regression, bootstrapping, trees, cluster analysis, survival analysis and so on
• Develop and articulate strategic recommendations based on rigorous data analysis
• Partner with client teams to understand business problems and marketing strategies
• MS in Statistics, Data Mining, Econometrics, Applied Mathematics, Computer Science or related fields or MBA (Preferred)
Must Have Skills:
• 1-3 years of analytics overall experience, including at least 1 years of quantitative analysis in the CMT/Telecom Industry
• Hands on experience in Predictive analytics projects involving statistical modeling, customer segmentation etc.
Good To Have Skills:
• Post Graduate degree in Statistics, Data Mining, Econometrics, Applied Mathematics, Computer Science or related field or MBA (Preferred)
• Experience of working with US/ overseas markets is preferable
• Exposure to Machine Learning with at least 1 year of practical experience in one or more approaches such as Random Forest, Neural Networks, Support Vector Machines, Gradient Boosting, Bayesian Networks, Deep Learning etc.