11+ Rational ClearCase Jobs in Delhi, NCR and Gurgaon | Rational ClearCase Job openings in Delhi, NCR and Gurgaon

A Delhi NCR based Applied AI & Consumer Tech company tackling one of the largest unsolved consumer internet problems of our time. We are a motley crew of smart, passionate and nice people who believe you can build a high performing company with a culture of respect aka a sports team with a heart aka a caring meritocracy.

Our illustrious angels include unicorn founders, serial entrepreneurs with exits, tech & consumer industry stalwarts and investment professionals/bankers.

We are hiring for our founding team (in Delhi NCR only, no remote) that will take the product from prototype to a landing! Opportunity for disproportionate non-linear impact, learning and wealth creation in a classic 0-1 with a Silicon Valley caliber founding team.

Key Responsibilities:

1.   Data Strategy and Vision:

·       Develop and drive the company's data analytics strategy, aligning it with overall business goals.

·       Define the vision for data analytics, outlining clear objectives and key results (OKRs) to measure success.

2.   Data Analysis and Interpretation:

·       Oversee the analysis of complex datasets to extract valuable insights, trends, and patterns.

·       Utilize statistical methods and data visualization techniques to present findings in a clear and compelling manner to both technical and non-technical stakeholders.

3.   Data Infrastructure and Tools:

·       Evaluate, select, and implement advanced analytics tools and platforms to enhance data processing and analysis capabilities.

·       Collaborate with IT teams to ensure a robust and scalable data infrastructure, including data storage, retrieval, and security protocols.

4.   Collaboration and Stakeholder Management:

·       Collaborate cross-functionally with teams such as marketing, sales, and product development to identify opportunities for data-driven optimizations.

·       Act as a liaison between technical and non-technical teams, ensuring effective communication of data insights and recommendations.

5.   Performance Measurement:

·       Establish key performance indicators (KPIs) and metrics to measure the impact of data analytics initiatives on business outcomes.

·       Continuously assess and improve the accuracy and relevance of analytical models and methodologies.

Qualifications:

• Bachelor's or Master's degree in Data Science, Statistics, Computer Science, or related field.
• Proven experience (5+ years) in data analytics, with a focus on leading analytics teams and driving strategic initiatives.
• Proficiency in data analysis tools such as Python, R, SQL, and advanced knowledge of data visualization tools.
• Strong understanding of statistical methods, machine learning algorithms, and predictive modelling techniques.
• Excellent communication skills, both written and verbal, to effectively convey complex findings to diverse audie 

AWS Glue Developer 

Work Experience: 6 to 8 Years

Work Location:  Noida, Bangalore, Chennai & Hyderabad

Must Have Skills: AWS Glue, DMS, SQL, Python, PySpark, Data integrations and Data Ops, 

Job Reference ID:BT/F21/IND

Job Description:

Design, build and configure applications to meet business process and application requirements.

Responsibilities:

7 years of work experience with ETL, Data Modelling, and Data Architecture Proficient in ETL optimization, designing, coding, and tuning big data processes using Pyspark Extensive experience to build data platforms on AWS using core AWS services Step function, EMR, Lambda, Glue and Athena, Redshift, Postgres, RDS etc and design/develop data engineering solutions. Orchestrate using Airflow.

Technical Experience:

Hands-on experience on developing Data platform and its components Data Lake, cloud Datawarehouse, APIs, Batch and streaming data pipeline Experience with building data pipelines and applications to stream and process large datasets at low latencies.

➢ Enhancements, new development, defect resolution and production support of Big data ETL development using AWS native services.

➢ Create data pipeline architecture by designing and implementing data ingestion solutions.

➢ Integrate data sets using AWS services such as Glue, Lambda functions/ Airflow.

➢ Design and optimize data models on AWS Cloud using AWS data stores such as Redshift, RDS, S3, Athena.

➢ Author ETL processes using Python, Pyspark.

➢ Build Redshift Spectrum direct transformations and data modelling using data in S3.

➢ ETL process monitoring using CloudWatch events.

➢ You will be working in collaboration with other teams. Good communication must.

➢ Must have experience in using AWS services API, AWS CLI and SDK

Professional Attributes:

➢ Experience operating very large data warehouses or data lakes Expert-level skills in writing and optimizing SQL Extensive, real-world experience designing technology components for enterprise solutions and defining solution architectures and reference architectures with a focus on cloud technology.

➢ Must have 6+ years of big data ETL experience using Python, S3, Lambda, Dynamo DB, Athena, Glue in AWS environment.

➢ Expertise in S3, RDS, Redshift, Kinesis, EC2 clusters highly desired.

Qualification:

➢ Degree in Computer Science, Computer Engineering or equivalent.

Salary: Commensurate with experience and demonstrated competence

What you will be doing:

As a part of the Global Credit Risk and Data Analytics team, this person will be responsible for carrying out analytical initiatives which will be as follows: -

• Dive into the data and identify patterns
• Development of end-to-end Credit models and credit policy for our existing credit products
• Leverage alternate data to develop best-in-class underwriting models
• Working on Big Data to develop risk analytical solutions
• Development of Fraud models and fraud rule engine
• Collaborate with various stakeholders (e.g. tech, product) to understand and design best solutions which can be implemented
• Working on cutting-edge techniques e.g. machine learning and deep learning models

Example of projects done in past:

• Lazypay Credit Risk model using CatBoost modelling technique ; end-to-end pipeline for feature engineering and model deployment in production using Python
• Fraud model development, deployment and rules for EMEA region

Basic Requirements:

• 1-3 years of work experience as a Data scientist (in Credit domain)
• 2016 or 2017 batch from a premium college (e.g B.Tech. from IITs, NITs, Economics from DSE/ISI etc)
• Strong problem solving and understand and execute complex analysis
• Experience in at least one of the languages - R/Python/SAS and SQL
• Experience in in Credit industry (Fintech/bank)
• Familiarity with the best practices of Data Science

Add-on Skills : 

• Experience in working with big data
• Solid coding practices
• Passion for building new tools/algorithms
• Experience in developing Machine Learning models