Data Science Manager

Job Description

Role & responsibilities 5+ years Hands on in Python and data science like tools pandas, NumPy, SciPy, matplotlib and strong exposure in regular expressions. 5+ years Hands on experience in Machine learning algorithms like SVM, CART, Bagging and Boosting algorithms, NLP based ML algorithms and Text mining. Hands on expertise to integrate multiple data sources in a streamlined pipeline. Strong knowledge in OOPs and creating custom python packages for serverless applications. Takes responsibility and ownership for work assignments, tasks and timelines. Functions as a "hands on" manager, engaging in the work with the team to stay relevant, current, as back-up and aware of the needs of the team. Provides transfer of knowledge to team members and support in learning. Demonstrates excellent written and verbal communication skills, strong analytical skills, and attention to detail. Strong Knowledge in SQL querying. Hands on experience in AWS services like Lambda, EC2, EMR, S3 and Athena, Batch, Textract and Comprehend. Strong Expertise in extracting text, tables, logos from low quality scanned multipage pdfs (80 - 150 dpi) and Images. Good Understanding in Probability and Statistics concepts and ability to find hidden patterns, relevant insights from the data. Expertise in Image Processing tools like OpenCV, scikit-image etc. Knowledge in Training NLP based Machine Learning and Deep Learning models to enhance and validate the text extraction process from Images and PDFs. Inquisitive thinking, passion to consistently learn and implement latest technologies and ability to manage multiple projects. Preferred candidate profile Balance team and individual responsibilities. Build analytic systems and predictive models. Build customer focused Next Best Action, Attribution & Segmentation models. Build, lead and orchestrate the global data science community. Coach, guide and direct teams of internal and vendor resources. Co-create with business / market / functions or IT platforms on requirements. Communicate complex analytical findings and implications to business leaders. Conduct and lead meetings and workshops to explain findings. Contribute to building a positive team spirit. Create alternative model approaches to assess complex model design and advance future capabilities. Design and build data set processes for modeling, data mining, and production purposes. Design and develop customized interactive reports and dashboards in Tableau. Design and develop machine learning / artificial intelligence (ML / AI) algorithms. Design and evaluate novel scalable approaches to experimentation. Design and implement prototypes using Python and Java programming language. Determine best format to execute ideas. Determine new ways to improve data and search quality, and predictive capabilities. Good to Have Knowledge in applying state of art NLP models like BERT, GPT - x, sciSpacy, Bidirectional LSTMs-CNN, RNN, AWS medical Comprehend for Clinical Named Entity Recognition (NER). Strong Leadership Skills. Deployment of custom trained and prebuilt NER models using AWS Sagemaker. Knowledge in setting up AWS Textract pipeline for large scale text processing using AWS SNS, AWS SQS, Lambda and EC2. Should have Intellectual curiosity to learn new things. ISMS responsibilities should be followed as per company policy.