Sr Data Science Specialist

1 week ago


Hyderabad, Telangana, India Cyient Full time ₹ 12,00,000 - ₹ 36,00,000 per year
  • 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.

Technical Role and Responsibilities

  • 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


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