<div>Description:</div><br> <div> Responsible for developing strategies for effective data analysis and reporting. Selects, configures, and implements analytical solutions. Develops and implements data analytics, data collection systems, and other strategies that optimize statistical efficiency and quality. Identifies, analyzes, and interprets trends or patterns in complex data sets. Monitors performance and quality control plans to identify performance. Works on problems of moderate and varied complexity where analysis of data may require adaptation of starndardized practices. Works with management to prioritize business and information needs. Bachelor's degree in computer science, information systems, statistics, or other related field. Ability to manage multiple assignments. Superior written and oral communication skills. 6-10+ years of experience. <br/> <br/> <br/>We are looking for a Senior Data Scientist who will be focused on the digital space, understanding the customer behavior as they travel through various channels and work on the customer journey analytics. <br/>The ideal candidate is adept at using large data sets to find opportunities for product and process optimization and using models to test the effectiveness of different courses of action. They must have strong experience using a variety of data mining/data analysis methods, using a variety of data tools, building and implementing models, using/creating algorithms and creating/running simulations. They must have a proven ability to drive business results with their data-based insights. The right candidate will have a passion for discovering solutions hidden in large data sets and working with stakeholders to improve business outcomes. <br/>You will work on Advanced Analytics using Big Data, Data Warehousing, Cognitive and Heuristic platforms. <br/> Research, design, implement, and oversee high-end analytical/technology process and solutions with a focus on leveraging advanced machine learning, artificial intelligence and cognitive methods. <br/> Work with the business to understand the requirements of the digital challenges, heuristic, machine and cognitive analysis and communicate back the results. <br/> Build analytical solutions and models by manipulating large data sets and integrating diverse data sources. <br/> Perform ad-hoc analysis and develop reproducible analytical approaches to meet business requirements. <br/> Perform exploratory and targeted data analyses using descriptive statistics and other methods. <br/> Apply machine learning and statistical techniques to large data sets to find actionable insights. <br/> Use complex algorithms to develop systems & applications that deliver business functions or architectural components. <br/> Present results and recommendations to senior management and business users. <br/> Responsible for providing line of sight to data quality and gaps where issues need to be addressed. <br/> Communicate the business value of technical solutions. <br/> <br/>You ll need to have: <br/> Bachelor s degree or eight or more years of work experience. <br/> Six or more years of relevant work experience. <br/> Experience working with and creating data architectures. <br/> Experience using statistical computer languages (Python, Scala, PySpark, Java, SQL, etc.) to manipulate data and draw insights from large data sets. <br/> Experience creating and using advanced machine learning algorithms and statistics: regression, simulation, scenario analysis, modeling, clustering, decision trees, neural networks, XGBoost, Genetic Algorithms etc. <br/> Deep Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications. <br/> Knowledge and experience in statistical and data mining techniques: GLM/Regression, Random Forest, Boosting, Trees, State Space,NLP, text mining, social network analysis, etc. <br/> Experience with Deep Learning using Tensorflow, Pytorch, Keras, etc. <br/> Experience with distributed data/computing tools: Tez, Map/Reduce, Hadoop, Hive, Spark etc. <br/> Knowledge and experience with ML model serializations like : PKL,RDS,PMML,ONNX and ML model deployments : Batch process, Real-time (End-point url) </div>
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