Sr Data Science Specialist

• Should have 10-15 years' hands-on experience in algorithms and implementation of analytics solutions in predictive analytics, text analytics and image analytics
• Expected to contribute to opportunity analysis, building project proposals, designing, implementation and execution across variety of ML projects in the areas of Predictive Modelling, Forecasting and Optimization
• Should have 5-10 years' of experience in leading a team of data scientists, works closely with client's technical team to plan, develop and execute on client requirements providing technical expertise and project leadership.
• Manage data science work streams and eventually build a team of data scientists, ML experts and data engineers to solve business problems by applying advanced Machine Learning algorithms and complex statistical models on large volumes of data.
• Work closely with product managers, software engineers, and infrastructure engineers to define strategy, roadmap and requirements
• Experience with information retrieval, Natural Language Processing, Natural Language Understanding and Neural Language Modeling.
• Ensure the data science team successfully delivers on design, development, testing, experimentation, and the operations of algorithms, data pipelines, and systems
• Follow industry best practices, stay up to date with and extend the state of the art in machine learning research and practice, drive innovation by contributing towards publications and patents.
• Regularly communicate with senior management on status, risk and strategy
• Collaborate to develop analytics pipelines in production systems around continuous integration and learning.
• Propose suitable technology stacks for projects to be deployed across cloud platforms and on-premises infrastructure.
• Evaluates and leads broad range of forward looking analytics initiatives, track emerging data science trends, and knowledge sharing
• Helps in new project proposals with advanced analytic architectures across functional areas as per requirement/opportunities.
• Participate in internal technical councils and represent the organization in forums that involve community of data scientists across industry and academia.

• Demonstrated strong capability in statistical/Mathematical modelling or Machine Learning or Artificial Intelligence
• Demonstrated skills in programming for implementation and deployment of algorithms preferably in Statistical/ML based programming languages in Python
• Experience leading enterprise-wide data science projects from scratch to scale
• Significant record of publications, exhibiting influence within an industry
• Sound Experience with traditional as well as modern statistical techniques, including Regression, Support Vector Machines, Regularization, Boosting, Random Forests, and other Ensemble Methods
• Highly proficient in Python, R, SQL, Spark, and other big data tools
• Visualization tool experience - preferably with Tableau or Power BI
• Sound knowledge of cloud ecosystems like Azure, AWS and Google cloud.
• Provide technical recommendations and engage with ETL/BI Architects, Business SMEs and other stakeholders throughout the Solution/Data Architecture and implementation lifecycle and recommend effective solutions to develop high performance and highly scalable data solutions (data marts/warehouse and data mining and advanced analytics)
• Experience in Big Data technologies like Hadoop, Spark, Hive, Pig, Presto, Cassandra, Kafka and NoSQL databases.
• Data analysis, reporting, visualization expertise and experience with tools such as Tableau, Alteryx, Python and R in scale.
• Carrying out statistical and mathematical modelling, solving complex business problems and delivering innovative solutions using state of the art tools and cutting-edge technologies for big data & beyond.
• Good understanding about statistics - hypothesis testing, p-values, confidence intervals, regression, t-test, f-test and ANOVA
• Domain experience in Storage, File systems, hybrid cloud environments is a plus.
• A critical thinker that can quickly understand a new problem space and apply analytic techniques to identify potential value
• Demonstrated thought leader with an interest in working on Digital Industrial transformation
• Ability to evaluate quality of ML models and to define the right performance metrics for models in accordance with the requirements of core platform
• Assist senior management in making key business decisions
• Experience in interpreting and communicating analytic results to analytical and non-analytical business partners and executive decision makers in a lucid, precise, clear way
• Strong knowledge on scalable ML model deployments with proficient experience on different tools like dockers, Azure, MLflow, Sagemaker and Kubernetes

Cyient