Data Scientist

Greetings from Ampcus!Ampcus Inc. is a Global leader in end-to-end IT Business Solutions and Services with latest technologies. We are listed among the top 50 fastest growing companies in USA. We work closely with our clients for Talent acquisition.Description:We are looking for a Data Scientist to join our Market Expansion team, responsible for driving profitability and growth across the company. As a Data Scientist, you will directly influence strategy, capital allocation, pricing, and operational initiatives affecting millions of customers and billions of dollars in revenue. You will work with all parts of the organization to identify opportunities, develop tools and strategies, and implement solutions leveraging data to improve profitability, efficiency, and customer experience. Your work will be analytical, but your intelligence, drive, and interpersonal skills will be just as important to your success. The opportunities you identify, initiatives you lead, and decisions you make will have direct, tangible impact on our customers, employees and company performance.Responsibilities: • Provide analytical support and recommendations regarding optimization of operational processes, capital allocation, and pricing.• Provide insights into future growth and profitability strategy through historical business analysis and forecasting of industry and major customer trends (e.g. what markets to prioritize, opportunities to pursue, how to win, impact of 5G, etc.)• Work with and analyze complex data from various sources. Manipulate large data sets and navigate a variety of servers, data types, and data structures to complete statistical and other analyses •Develop predictive and descriptive models using advanced procedures like statistical modeling, linear regression and Bayesian analyses. Knowledge of some/all of the following techniques: Multivariate Regression, Logistic Regression, Support Vector Machines, Bootstrap Aggregation, Boosting, Decision Trees, and Time Series Analysis.• Use a suite of analytical tools including Python, SAS & R to build, implement, and regularly monitor the effectiveness of predictive models.• Perform statistical data analysis and build forecasting and optimization models.• Develop and monitor industry trends, to support the monitoring, evaluation and development of current and newly emerging products, and consumer behavior.• Collaborating with business analysts to gather requirements and translate to actionable scenarios and models.• Work with various functions to document and communicate results of analyses, present work in clean, structured formats.Required Skills/Requirements:• Experience developing and implementing statistical models.• Experience with a statistical analysis tool like Python.• Experience performing data management, mining, and manipulation along with analytics.• Experience using SQL in a RDBMS environment.• Excellent communication skills, oral and written.• Must have strong attention to detail and ability to work independently under general instructions and with a team.• Some programming experience - This role will rely heavily on programming experience in Python, as well as SSMS• Degree (Graduate / Ph.D. preferred) in an analytical or technical field (e.g. applied mathematics, physics, computer science, operations research).• Act as a liaison between consumer, network and finance stakeholders.• Develop and maintain training material.• Represent modeling on teams and task groups for projects/initiatives across the organization and act as a source of effective challenge.• Perform outreach activities to new business areas engaged in modeling • Develop and maintain business unit and enterprise-wide model risk metrics and reports • Develop and maintain model repository, develop model scorecard, and communicate model impact to senior leaders.• Lead building out action plans and milestones to drive remediation of any oversight issues.• Lead Modeling team’s communication for regulatory exams.• Drive knowledge sharing on relevant industry standards, best practices, and business processes and technology used in model risk management and model development. • Lead evaluation of model management technology tools.Desirable:• Experience with tools and methodologies specific to big data• Familiarity with relational databases, such as Oracle, MS SQL and Server• Telecommunications Background, Financial Background, Python/SQL,R/Cloud, Data science methodologies, Churn modeling, Propensity, Geospatial• ETL• Communication – coherent expression of thought and understanding of objective/questionDegree Requirements: Degree (Graduate / Ph.D. preferred) in an analytical or technical field (e.g. applied mathematics, physics, computer science, operations research).