Lead Data Scientist Jobs

Job descriptionJob Overview: We are seeking a Lead Data Engineer (AWS) with 5-6 / 5+ years of experience in AWS Cloud platform, ETL development, and data processing tools. This role involves monitoring and supporting application workflows, ensuring system connectivity and performance. The ideal candidate should have hands-on experience with in depth knowledge on AWS services, AWS Glue, Redshift, Airflow, and other data processing tools such as Spark, with the ability to guide and mentor a team in a collaborative environment. This role requires leading a team to uphold operational standards hence the candidate should have experience handling a team. CTC / Budget allocated for (Lead-Data Engineer): 11-12 LPA (for deserving candidates)Primary Responsibilities:Application Monitoring & Workflow Management: Oversee job monitoring, application flow, and system connectivity to ensure smooth operations.Utilizing AWS Glue and Redshift for data processingCandidate should possess strong knowledge in AWS Glue, Redshift, and Airflow processes and should be able to resolve bottlenecks or issues.Retrigger failed jobs and manage job orchestration through Airflow for timely task completion.Cloud Monitoring & Notifications:Utilize AWS CloudWatch to monitor system health, performance, and job status.Setup AWS Push Notifications to alert the team to system issues, such as database downtime or performance degradation.

Data Scientist Program Embedded Job Description: We are seeking a highly skilled and motivated senior data scientist to support a big data program. The successful candidate will play a pivotal role in supporting multiple projects in this program covering traditional tasks from revenue management, demand forecasting, improving customer experience to testing/using new tools/platforms such as Copilot Fabric for different purpose. The expected candidate would have deep expertise in machine learning methodology and applications. And he/she should have completed multiple large scale data science projects (full cycle from ideation to BAU). Beyond technical expertise, problem solving in complex set-up will be key to the success for this role. This is a data science role directly embedded into the program/projects, stake holder management and collaborations with patterner are crucial to the success on this role (on top of the deep expertise). What we are looking for: Highly efficient in Python/Pyspark/R. Understand MLOps concepts, working experience in product industrialization (from Data Science point of view). Experience in building product for live deployment, and continuous development and continuous integration. Familiar with cloud platforms such as Azure, GCP, and the data management systems on such platform. Familiar with Databricks and product deployment on Databricks. Experience in ML projects involving techniques: Regression, Time Series, Clustering, Classification, Dimension Reduction, Anomaly detection with traditional ML approaches and DL approaches. Solid background in statistics, probability distributions, A/B testing validation, univariate/multivariate analysis, hypothesis test for different purpose, data augmentation etc. Familiar with designing testing framework for different modelling practice/projects based on business needs. Exposure to Gen AI tools and enthusiastic about experimenting and have new ideas on what can be done.