Lead Data Scientist

Job Description

* Duties and Responsibilities - 3. PRINCIPAL ACCOUNTABILITIES (Accountabilities associated with the job) Translate business questions into clear and solvable data science problems Maximize value of existing data assets Develop data driven algorithms to solve complex business problem. Extract actionable hidden patterns clusters commonalities and insights from large and complex data sets. Operationalize data driven solutions using sound Software Engineering Machine Learning and AI practice 4. MAJOR CHALLENGES (Challenges faced on an on-going basis in carrying out the job) Understand BFL Enterprise Data & various functional linkages Working with business on translating broad problem statements to solvable data science problems Ensuring capability delivery working with various support & business functions Understand Data Science Algorithms & Coding complexities pre-processing and feature engineering to problem modeling and Hyper parameter tuning. Deploying AI solution at scale. 5. DECISIONS (Key decisions taken by job holder at his/her end) Implementation approach for scalability Effective AI/ML technical & infrastructure Solution Approach AI model integration and deployment approach 6. INTERACTIONS (Key working relationships a job holder needs to have INSIDE and OUTSIDE the company to accomplish the job) Internal Clients Roles you need to interact with inside the organization to enable success in your day to day work Business Business COE Teams Technology teams External Clients Roles you need to interact with outside the organization to enable success in your day to day work Large enterprise technology partners 7. DIMENSIONS (Key numerical data which will reflect the scope and scale of activities concerning this job) Financial Dimensions (These should be quantifiable numerical amounts) Basis specific business projects success criteria for model & capability deployments may be factored Other Dimensions (Significant volume dimensions associated with the job) Total Team Size: 1 Number of Direct Reports:0 Number of Indirect Reports:0 Number of Outsourced employees:0 Number of locations: NA Number of products: NA , * SKILLS AND KNOWLEDGE (Minimum acceptable proficiency for this job which best indicates the education and/or experience requirements of this job and not the incumbent) Educational Qualifications Qualifications 1. Educational - PhD/MTech/BE/ BTech/MSc in CS or Math, Operation research, Statistics, Econometrics or in any quantitative field 2. 6+ years of industrial experience in analytics, predictive modeling, Machine learning, NLP, predictive analytics solution development and deployment 3. Should have strong experience in anyone or more programming languages Python or JAVA. Experience in RESTful, Web Services 4. Experience in using Python, R, SAS or any other statistical software (plus other open-source libraries) kills with Shell/Perl (or similar scripting language), Scala and Java 5. Hands-on Experience with broad range of machine learning/deep learning tools e.g. TensorFlow, Spark, Theano, PyTorch, scikit-learn, Keras, Caffe and Collaboration environments (e.g. Jupyter Notebook, Pycharm). Extensive in designing solutions that optimize ML performance by through advance HW and Software techniques. 6. Hands-on experience of API Integration single-sign -on and token-based authentication. Experience integrating with SQL and NoSQL databases (Cosmos DB, Cassandra, MongoDB) 7. Good understanding of DevOps pipeline like Azure Devops. Experience in Agile environment 8. Experience Container Orchestration technologies (Kubernetes), distributed systems, scalable data analytics technologies (Spark) 9. Skills with Relational Databases, Data warehouses, Structured & Unstructured data forms. 10. Solid knowledge in deep learning algorithms and AI system design and architecture. Position Summary: We are looking for an exceptional hands-on Artificial Intelligence Engineer with a proven track record of experience in applying techniques like knowledge representation and reasoning (KRR), Natural language processing (NLP), speech recognition, Computer vision and/or machine learning/ AI and deep learning/complex algorithms. Ability to easily go from idea to working prototype in Python, Java and or Scala. Experience with Hadoop, Spark. Large Scale Machine Learning Algorithms and infrastructure that powers our alternative data strategy. Experience in building end-to-end state -of -art Machine Learning system that serve production traffic. Proven experience of driving incremental value and repeatable growth through products and services directly tied to machine learning techniques and technologies. Ability to produce robust production quality code incorporating testing, evaluations, and monitoring. Collaborate with fellow data scientists and Engineers to implement effective and specific methodologies. Generate and present clear and concise reports. Ability to develop and implement deep learning algorithms to address real business problems. Implement best- practice for maintainable software development including but not limited to: Continuous integration, build, release, deployment process, management services in various environments, documentation, adherence to improvement of coding standard

Keyskills :
analyticsbankingbusiness intelligenceclusteringcustomer relationsnatural language processingweb servicesdata sciencesystem design