Data Analyst Lead

As a part of WWS, your expertise in machine learning helps us extract value from our data. You will lead all the processes from data collection, cleaning, and preprocessing, to training models and situating them to production. The ideal candidate will be passionate about artificial intelligence and stay up-to-date with the latest developments in the field.

What We Expect

• A Bachelor's/Master's degree in IT, computer science, or an advanced related field is preferred.

• At least 3+ years of experience working with ML libraries and packages.

• Familiarity with coding and programming languages, including Python, Java, C++, and SAS.

• Strong experience in programming and statistics.

• Well-versed in Data Science and neural schematics in networking and software.

• Flexibility in shifts is appreciated.

A Full Stack Developer’s Ideal Day At WWS

Design and Develop. The primary protocols include implementing machine learning algorithms and running AI systems experiments and tests. The Designing and development of machine learning systems along with performing statistical analyses falls under day to day activities of the developer.

Algorithm Assertion. The engineers act as critical members of the data science team as their tasks involve researching, asserting, and designing the artificial intelligence responsible for machine learning and maintaining and improving existing artificial intelligence systems.

Research and Development. To analyze large, complex datasets and extract insights and decide on the appropriate technique. research and implement best practices to improve the existing machine learning infrastructure. At most providing support to engineers and product managers in implementing machine learning as the product.

What You Can Expect

• Full-time, salaried positions creamed with welfare programs.

• Competitive salary and tailored training in the core space with recognition potential and annual bonus.

• Periodic performance appraisals.

• Attendance Incentives.

• Working with the best and budding talent in the industry.

• A conducive intangible environment with dynamic benefits.

Why Consider Machine Learning Engineer as a career with WWS?

With a very appealing work environment at WWS, our setting made it easier to build relationships with other staff members and clients. You may also have an opportunity to learn other aspects of environmental office work on the job, which can enhance your experience and qualifications.

Many businesses must proactively react to changing factors — like patterns of customer behavior or prices. Tracking model performance and retraining it once fresher data is available is key to success. This falls under the MLE range of responsibilities for which the requirement has been crucial for many organizations.

Please attach your resume and let us know through email your current address, phone number, and the best time to contact you by phone.

                                          Apply To this Job

We are seeking a skilled AWS ETL/ELT Data Architect with a specialization in MongoDB to join our team. The ideal candidate will possess comprehensive knowledge and hands-on experience

in designing, implementing, and managing ETL/ELT processes within AWS while also demonstrating proficiency in MongoDB database management.

This role requires expertise in data architecture, AWS services, and MongoDB to optimize data solutions effectively.

Responsibilities:

● Design, architect, and implement ETL/ELT processes within AWS, integrating data from various sources into data lakes or warehouses, and utilising MongoDB as part of the data ecosystem.

● Collaborate cross-functionally to assess data requirements, analyze sources, and strategize effective data integration within AWS environments, considering MongoDB's role in the architecture.

● Construct scalable and high-performance data pipelines within AWS while integrating MongoDB for optimal data storage, retrieval, and manipulation.

● Develop comprehensive documentation covering data architecture, flows, and the interplay between AWS services, MongoDB, and ETL/ELT processes from scratch.

● Perform thorough data profiling, validation, and troubleshooting, ensuring data accuracy, consistency, and integrity in conjunction with MongoDB management.

● Stay updated with AWS and MongoDB best practices, emerging technologies, and industry trends to propose innovative data solutions and implementations.

● Provide mentorship to junior team members and foster collaboration with stakeholders to deliver robust data solutions.

● Analyze data issues, identify and articulate the business impact of data problems

● Perform code reviews and ensure that all solutions are aligned with pre-defined architectural standards, guidelines, and best practices, and meet quality standards

Qualifications:

● Bachelor's or Master’s degree in Computer Science, Information Technology, or related field.

● Minimum 5 years of hands-on experience in ETL/ELT development, data architecture, or similar roles.

● Having implemented more than a minimum of 3-4 live projects in a similar field would be desirable.

● Expertise in designing and implementing AWS-based ETL/ELT processes using tools like AWS Glue, AWS Data Pipeline, etc.

• Experience with Cloud native Data tools/Services such as AWS Athena, AWS Glue, Redshift Spectrum, AWS EMR, AWS Aurora, Big Query, Big Table, S3, etc.

• Strong programming skills in at least one of the following languages: Java, Scala, C++.

• Familiarity with a scripting language like Python as well as Unix/Linux shells.

• Comfortable with multiple AWS components including RDS, AWS Lambda, AWS Glue, AWS Athena, EMR. Equivalent tools in the GCP stack will also suffice.

• Strong analytical skills and advanced SQL knowledge, indexing, query optimization techniques.

• Experience implementing software around data processing, metadata management, and ETL pipeline tools like Airflow.

Experience with the following software/tools is highly desired:

• Apache Spark, Kafka, Hive, etc.

• SQL and NoSQL databases like MySQL, Postgres, DynamoDB.

• Workflow management tools like Airflow.

• AWS cloud services: RDS, AWS Lambda, AWS Glue, AWS Athena, EMR.

• Familiarity with Spark programming paradigms (batch and stream-processing).

• RESTful API services.

Role: Principal Software Engineer

We looking for a passionate Principle Engineer - Analytics to build data products that extract valuable business insights for efficiency and customer experience. This role will require managing, processing and analyzing large amounts of raw information and in scalable databases. This will also involve developing unique data structures and writing algorithms for the entirely new set of products. The candidate will be required to have critical thinking and problem-solving skills. The candidates must be experienced with software development with advanced algorithms and must be able to handle large volume of data. Exposure with statistics and machine learning algorithms is a big plus. The candidate should have some exposure to cloud environment, continuous integration and agile scrum processes.

Responsibilities:

• Lead projects both as a principal investigator and project manager, responsible for meeting project requirements on schedule

• Software Development that creates data driven intelligence in the products which deals with Big Data backends

• Exploratory analysis of the data to be able to come up with efficient data structures and algorithms for given requirements

• The system may or may not involve machine learning models and pipelines but will require advanced algorithm development

• Managing, data in large scale data stores (such as NoSQL DBs, time series DBs, Geospatial DBs etc.)

• Creating metrics and evaluation of algorithm for better accuracy and recall

• Ensuring efficient access and usage of data through the means of indexing, clustering etc.

• Collaborate with engineering and product development teams.

Requirements:

• Master’s or Bachelor’s degree in Engineering in one of these domains - Computer Science, Information Technology, Information Systems, or related field from top-tier school

• OR Master’s degree or higher in Statistics, Mathematics, with hands on background in software development.

• Experience of 8 to 10 year with product development, having done algorithmic work

• 5+ years of experience working with large data sets or do large scale quantitative analysis

• Understanding of SaaS based products and services.

• Strong algorithmic problem-solving skills

• Able to mentor and manage team and take responsibilities of team deadline.

Skill set required:

• In depth Knowledge Python programming languages

• Understanding of software architecture and software design

• Must have fully managed a project with a team

• Having worked with Agile project management practices

• Experience with data processing analytics and visualization tools in Python (such as pandas, matplotlib, Scipy, etc.)

• Strong understanding of SQL and querying to NoSQL database (eg. Mongo, Casandra, Redis

Job Description:

The data science team is responsible for solving business problems with complex data. Data complexity could be characterized in terms of volume, dimensionality and multiple touchpoints/sources. We understand the data, ask fundamental-first-principle questions, apply our analytical and machine learning skills to solve the problem in the best way possible. 

Our ideal candidate

The role would be a client facing one, hence good communication skills are a must. 

The candidate should have the ability to communicate complex models and analysis in a clear and precise manner. 

The candidate would be responsible for:

• Comprehending business problems properly - what to predict, how to build DV, what value addition he/she is bringing to the client, etc.
• Understanding and analyzing large, complex, multi-dimensional datasets and build features relevant for business
• Understanding the math behind algorithms and choosing one over another
• Understanding approaches like stacking, ensemble and applying them correctly to increase accuracy

Desired technical requirements

• Proficiency with Python and the ability to write production-ready codes. 
• Experience in pyspark, machine learning and deep learning
• Big data experience, e.g. familiarity with Spark, Hadoop, is highly preferred
• Familiarity with SQL or other databases.

Role: Data Engineer  
Company: PayU

Location: Bangalore/ Mumbai

Experience : 2-5 yrs

About Company:

PayU is the payments and fintech business of Prosus, a global consumer internet group and one of the largest technology investors in the world. Operating and investing globally in markets with long-term growth potential, Prosus builds leading consumer internet companies that empower people and enrich communities.

The leading online payment service provider in 36 countries, PayU is dedicated to creating a fast, simple and efficient payment process for merchants and buyers. Focused on empowering people through financial services and creating a world without financial borders where everyone can prosper, PayU is one of the biggest investors in the fintech space globally, with investments totalling $700 million- to date. PayU also specializes in credit products and services for emerging markets across the globe. We are dedicated to removing risks to merchants, allowing consumers to use credit in ways that suit them and enabling a greater number of global citizens to access credit services.

Our local operations in Asia, Central and Eastern Europe, Latin America, the Middle East, Africa and South East Asia enable us to combine the expertise of high growth companies with our own unique local knowledge and technology to ensure that our customers have access to the best financial services.

India is the biggest market for PayU globally and the company has already invested $400 million in this region in last 4 years. PayU in its next phase of growth is developing a full regional fintech ecosystem providing multiple digital financial services in one integrated experience. We are going to do this through 3 mechanisms: build, co-build/partner; select strategic investments. 

PayU supports over 350,000+ merchants and millions of consumers making payments online with over 250 payment methods and 1,800+ payment specialists. The markets in which PayU operates represent a potential consumer base of nearly 2.3 billion people and a huge growth potential for merchants. 

Job responsibilities:

• Design infrastructure for data, especially for but not limited to consumption in machine learning applications 
• Define database architecture needed to combine and link data, and ensure integrity across different sources 
• Ensure performance of data systems for machine learning to customer-facing web and mobile applications using cutting-edge open source frameworks, to highly available RESTful services, to back-end Java based systems 
• Work with large, fast, complex data sets to solve difficult, non-routine analysis problems, applying advanced data handling techniques if needed 
• Build data pipelines, includes implementing, testing, and maintaining infrastructural components related to the data engineering stack.
• Work closely with Data Engineers, ML Engineers and SREs to gather data engineering requirements to prototype, develop, validate and deploy data science and machine learning solutions

Requirements to be successful in this role: 

• Strong knowledge and experience in Python, Pandas, Data wrangling, ETL processes, statistics, data visualisation, Data Modelling and Informatica.
• Strong experience with scalable compute solutions such as in Kafka, Snowflake
• Strong experience with workflow management libraries and tools such as Airflow, AWS Step Functions etc. 
• Strong experience with data engineering practices (i.e. data ingestion pipelines and ETL) 
• A good understanding of machine learning methods, algorithms, pipelines, testing practices and frameworks 
• Preferred) MEng/MSc/PhD degree in computer science, engineering, mathematics, physics, or equivalent (preference: DS/ AI) 
• Experience with designing and implementing tools that support sharing of data, code, practices across organizations at scale 

• Use data to develop machine learning models that optimize decision making in Credit Risk, Fraud, Marketing, and Operations
• Implement data pipelines, new features, and algorithms that are critical to our production models
• Create scalable strategies to deploy and execute your models
• Write well designed, testable, efficient code
• Identify valuable data sources and automate collection processes.
• Undertake to preprocess of structured and unstructured data.
• Analyze large amounts of information to discover trends and patterns.

Requirements:

• 1+ years of experience in applied data science or engineering with a focus on machine learning
• Python expertise with good knowledge of machine learning libraries, tools, techniques, and frameworks (e.g. pandas, sklearn, xgboost, lightgbm, logistic regression, random forest classifier, gradient boosting regressor etc)
• strong quantitative and programming skills with a product-driven sensibility

• Desire to explore new technology and break new ground.
• Are passionate about Open Source technology, continuous learning, and innovation.
• Have the problem-solving skills, grit, and commitment to complete challenging work assignments and meet deadlines.

Qualifications

• Engineer enterprise-class, large-scale deployments, and deliver Cloud-based Serverless solutions to our customers.
• You will work in a fast-paced environment with leading microservice and cloud technologies, and continue to develop your all-around technical skills.
• Participate in code reviews and provide meaningful feedback to other team members.
• Create technical documentation.
• Develop thorough Unit Tests to ensure code quality.

Skills and Experience

• Advanced skills in troubleshooting and tuning AWS Lambda functions developed with Java and/or Python.
• Experience with event-driven architecture design patterns and practices
• Experience in database design and architecture principles and strong SQL abilities
• Message brokers like Kafka and Kinesis
• Experience with Hadoop, Hive, and Spark (either PySpark or Scala)
• Demonstrated experience owning enterprise-class applications and delivering highly available distributed, fault-tolerant, globally accessible services at scale.
• Good understanding of distributed systems.
• Candidates will be self-motivated and display initiative, ownership, and flexibility.

Preferred Qualifications

• AWS Lambda function development experience with Java and/or Python.
• Lambda triggers such as SNS, SES, or cron.
• Databricks
• Cloud development experience with AWS services, including:
• IAM
• S3
• EC2
• AWS CLI
• API Gateway
• ECR
• CloudWatch
• Glue
• Kinesis
• DynamoDB
• Java 8 or higher
• ETL data pipeline building
• Data Lake Experience
• Python
• Docker
• MongoDB or similar NoSQL DB.
• Relational Databases (e.g., MySQL, PostgreSQL, Oracle, etc.).
• Gradle and/or Maven.
• JUnit
• Git
• Scrum
• Experience with Unix and/or macOS.
• Immediate Joiners

Nice to have:

• AWS / GCP / Azure Certification.
• Cloud development experience with Google Cloud or Azure