Data Scientist (Risk)/Sr. Data Scientist (Risk)
As a part of the Data science/Analytics team at Rupifi, you will play a significant role in helping define the business/product vision and deliver it from the ground up by working with passionate high-performing individuals in a very fast-paced working environment.
You will work closely with Data Scientists & Analysts, Engineers, Designers, Product Managers, Ops Managers and Business Leaders, and help the team make informed data driven decisions and deliver high business impact.
Preferred Skills & Responsibilities:
- Analyze data to better understand potential risks, concerns and outcomes of decisions.
- Aggregate data from multiple sources to provide a comprehensive assessment.
- Past experience of working with business users to understand and define inputs for risk models.
- Ability to design and implement best in class Risk Models in Banking & Fintech domain.
- Ability to quickly understand changing market trends and incorporate them into model inputs.
- Expertise in statistical analysis and modeling.
- Ability to translate complex model outputs into understandable insights for business users.
- Collaborate with other team members to effectively analyze and present data.
- Conduct research into potential clients and understand the risks of accepting each one.
- Monitor internal and external data points that may affect the risk level of a decision.
- Hands-on experience in Python & SQL.
- Hands-on experience in any visualization tool preferably Tableau
- Hands-on experience in Machine & Deep Learning area
- Experience in handling complex data sources
- Experience in modeling techniques in the fintech/banking domain
- Experience of working on Big data and distributed computing.
- A BTech/BE/MSc degree in Math, Engineering, Statistics, Economics, ML, Operations Research, or similar quantitative field.
- 3 to 10 years of modeling experience in the fintech/banking domain in fields like collections, underwriting, customer management, etc.
- Strong analytical skills with good problem solving ability
- Strong presentation and communication skills
- Experience in working on advanced machine learning techniques
- Quantitative and analytical skills with a demonstrated ability to understand new analytical concepts.
- Designing and implementing fine-tuned production ready data/ML pipelines in Hadoop platform.
- Driving optimization, testing and tooling to improve quality.
- Reviewing and approving high level & amp; detailed design to ensure that the solution delivers to the business needs and aligns to the data & analytics architecture principles and roadmap.
- Understanding business requirements and solution design to develop and implement solutions that adhere to big data architectural guidelines and address business requirements.
- Following proper SDLC (Code review, sprint process).
- Identifying, designing, and implementing internal process improvements: automating manual processes, optimizing data delivery, etc.
- Building robust and scalable data infrastructure (both batch processing and real-time) to support needs from internal and external users.
- Understanding various data security standards and using secure data security tools to apply and adhere to the required data controls for user access in the Hadoop platform.
- Supporting and contributing to development guidelines and standards for data ingestion.
- Working with a data scientist and business analytics team to assist in data ingestion and data related technical issues.
- Designing and documenting the development & deployment flow.
- Experience in developing rest API services using one of the Scala frameworks.
- Ability to troubleshoot and optimize complex queries on the Spark platform
- Expert in building and optimizing ‘big data’ data/ML pipelines, architectures and data sets.
- Knowledge in modelling unstructured to structured data design.
- Experience in Big Data access and storage techniques.
- Experience in doing cost estimation based on the design and development.
- Excellent debugging skills for the technical stack mentioned above which even includes analyzing server logs and application logs.
- Highly organized, self-motivated, proactive, and ability to propose best design solutions.
- Good time management and multitasking skills to work to deadlines by working independently and as a part of a team.
Client An IT Services Major, hiring for a leading insurance player.
Position: SENIOR CONSULTANT
- Azure admin- senior consultant with HD Insights(Big data)
Skills and Experience
- Microsoft Azure Administrator certification
- Bigdata project experience in Azure HDInsight Stack. big data processing frameworks such as Spark, Hadoop, Hive, Kafka or Hbase.
- Preferred: Insurance or BFSI domain experience
- 5 to 5 years of experience is required.
We are looking for an outstanding Big Data Engineer with experience setting up and maintaining Data Warehouse and Data Lakes for an Organization. This role would closely collaborate with the Data Science team and assist the team build and deploy machine learning and deep learning models on big data analytics platforms.
Roles and Responsibilities:
- Develop and maintain scalable data pipelines and build out new integrations and processes required for optimal extraction, transformation, and loading of data from a wide variety of data sources using 'Big Data' technologies.
- Develop programs in Scala and Python as part of data cleaning and processing.
- Assemble large, complex data sets that meet functional / non-functional business requirements and fostering data-driven decision making across the organization.
- Responsible to design and develop distributed, high volume, high velocity multi-threaded event processing systems.
- Implement processes and systems to validate data, monitor data quality, ensuring production data is always accurate and available for key stakeholders and business processes that depend on it.
- Perform root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
- Provide high operational excellence guaranteeing high availability and platform stability.
- Closely collaborate with the Data Science team and assist the team build and deploy machine learning and deep learning models on big data analytics platforms.
- Experience with Big Data pipeline, Big Data analytics, Data warehousing.
- Experience with SQL/No-SQL, schema design and dimensional data modeling.
- Strong understanding of Hadoop Architecture, HDFS ecosystem and eexperience with Big Data technology stack such as HBase, Hadoop, Hive, MapReduce.
- Experience in designing systems that process structured as well as unstructured data at large scale.
- Experience in AWS/Spark/Java/Scala/Python development.
- Should have Strong skills in PySpark (Python & SPARK). Ability to create, manage and manipulate Spark Dataframes. Expertise in Spark query tuning and performance optimization.
- Experience in developing efficient software code/frameworks for multiple use cases leveraging Python and big data technologies.
- Prior exposure to streaming data sources such as Kafka.
- Should have knowledge on Shell Scripting and Python scripting.
- High proficiency in database skills (e.g., Complex SQL), for data preparation, cleaning, and data wrangling/munging, with the ability to write advanced queries and create stored procedures.
- Experience with NoSQL databases such as Cassandra / MongoDB.
- Solid experience in all phases of Software Development Lifecycle - plan, design, develop, test, release, maintain and support, decommission.
- Experience with DevOps tools (GitHub, Travis CI, and JIRA) and methodologies (Lean, Agile, Scrum, Test Driven Development).
- Experience building and deploying applications on on-premise and cloud-based infrastructure.
- Having a good understanding of machine learning landscape and concepts.
Qualifications and Experience:
Engineering and post graduate candidates, preferably in Computer Science, from premier institutions with proven work experience as a Big Data Engineer or a similar role for 3-5 years.
Good to have at least one of the Certifications listed here:
AZ 900 - Azure Fundamentals
DP 200, DP 201, DP 203, AZ 204 - Data Engineering
AZ 400 - Devops Certification
Roles and responsibilities:
- Responsible for development and maintenance of applications with technologies involving Enterprise Java and Distributed technologies.
- Experience in Hadoop, Kafka, Spark, Elastic Search, SQL, Kibana, Python, experience w/ machine learning and Analytics etc.
- Collaborate with developers, product manager, business analysts and business users in conceptualizing, estimating and developing new software applications and enhancements..
- Collaborate with QA team to define test cases, metrics, and resolve questions about test results.
- Assist in the design and implementation process for new products, research and create POC for possible solutions.
- Develop components based on business and/or application requirements
- Create unit tests in accordance with team policies & procedures
- Advise, and mentor team members in specialized technical areas as well as fulfill administrative duties as defined by support process
- Work with cross-functional teams during crisis to address and resolve complex incidents and problems in addition to assessment, analysis, and resolution of cross-functional issues.
Knowledge of Hadoop ecosystem installation, initial-configuration and performance tuning.
Expert with Apache Ambari, Spark, Unix Shell scripting, Kubernetes and Docker
Knowledge on python would be desirable.
Experience with HDP Manager/clients and various dashboards.
Understanding on Hadoop Security (Kerberos, Ranger and Knox) and encryption and Data masking.
Experience with automation/configuration management using Chef, Ansible or an equivalent.
Strong experience with any Linux distribution.
Basic understanding of network technologies, CPU, memory and storage.
Database administration a plus.
Qualifications and Education Requirements
2 to 4 years of experience with and detailed knowledge of Core Hadoop Components solutions and
dashboards running on Big Data technologies such as Hadoop/Spark.
Bachelor degree or equivalent in Computer Science or Information Technology or related fields.
- Previous experience of working in large scale data engineering
- 4+ years of experience working in data engineering and/or backend technologies with cloud experience (any) is mandatory.
- Previous experience of architecting and designing backend for large scale data processing.
- Familiarity and experience of working in different technologies related to data engineering – different database technologies, Hadoop, spark, storm, hive etc.
- Hands-on and have the ability to contribute a key portion of data engineering backend.
- Self-inspired and motivated to drive for exceptional results.
- Familiarity and experience working with different stages of data engineering – data acquisition, data refining, large scale data processing, efficient data storage for business analysis.
- Familiarity and experience working with different DB technologies and how to scale them.
- End to end responsibility to come up with data engineering architecture, design, development and then implementation of it.
- Build data engineering workflow for large scale data processing.
- Discover opportunities in data acquisition.
- Bring industry best practices for data engineering workflow.
- Develop data set processes for data modelling, mining and production.
- Take additional tech responsibilities for driving an initiative to completion
- Recommend ways to improve data reliability, efficiency and quality
- Goes out of their way to reduce complexity.
- Humble and outgoing - engineering cheerleaders.