Senior Analytic Consultant

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

2+ years of experience in a Data Engineer role.
● Proficiency in Linux.
● Experience working with AWS cloud services: EC2, S3, RDS, Redshift.
● Must have SQL knowledge and experience working with relational databases, query
authoring (SQL) as well as familiarity with databases including Mysql, Mongo, Cassandra,
and Athena.
● Must have experience with Python/Scala.
● Must have experience with Big Data technologies like Apache Spark.
● Must have experience with Apache Airflow.
● Experience with data pipelines and ETL tools like AWS Glue.

Founders are the alumnus of IIT-D, IIM-B and Wharton. They’ve 12+ years of experience as Venture capital and corporate entrepreneurship at DFJ, Vertex, InMobi and VP at Snyder UAE, investment banking at Unitus Capital - leading the financial services practice, and institutional equities at Kotak. They’ve a team of high-quality professionals coming together for this mission to disrupt the convention. AsData Scientist, you will develop a first of its kind risk engine for revenue-based financing in India and automating investment appraisals for the company's different revenue-based financing products

What you will do:

 

 

Desired Candidate Profile

 

What you need to have:

If you are interested in joining a purpose-driven community that is dedicated to creating ambitious and inclusive workplaces, then be a part of a high growth startup with a world class team, building a revolutionary product!

Our client is a vertical fintech play focused on solving industry-specific financing gaps in the food sector through the application of data. The platform provides skin-in-the-game growth capital to much-loved F&B brands. Founded in 2019, they're VC funded and based out of Singapore and India-Bangalore.

Founders are the alumnus of IIT-D, IIM-B and Wharton. They have 12+ years of experience as Venture capital and corporate entrepreneurship at DFJ, Vertex, InMobi, VP at Snyder UAE, investment banking at Unitus Capital - leading the financial services practice, and institutional equities at Kotak. They've a team of high-quality professionals coming together for this mission to disrupt the convention.

As a Data Analyst - Underwriting & Risk, you will be developing a first of its kind risk engine for revenue-based financing in India and automating investment appraisals for the company's different revenue-based financing products

What you will do:

 

What you need to have:

Responsibilities

* Formulates and recommends standards for achieving maximum performance

and efficiency of the DW ecosystem.

* Participates in the Pre-sales activities for solutions of various customer

problem-statement/situations.

* Develop business cases and ROI for the customer/clients.

* Interview stakeholders and develop BI roadmap for success given project

prioritization

* Evangelize self-service BI and visual discovery while helping to automate any

manual process at the client site.

* Work closely with the Engineering Manager to ensure prioritization of

customer deliverables.

* Champion data quality, integrity, and reliability throughout the organization by

designing and promoting best practices.

 *Implementation 20%

* Help DW/DE team members with issues needing technical expertise or

complex systems and/or programming knowledge.

* Provide on-the-job training for new or less experienced team members.

* Develop a technical excellence team

Requirements

- experience designing business intelligence solutions

- experience with ETL Process, Data warehouse architecture

- experience with Azure Data services i.e., ADF, ADLS Gen 2, Azure SQL dB,

Synapse, Azure Databricks, and Power BI

- Good analytical and problem-solving skills

- Fluent in relational database concepts and flat file processing concepts

- Must be knowledgeable in software development lifecycles/methodologies

• Create and maintain optimal data pipeline architecture,
• Assemble large, complex data sets that meet functional / non-functional business requirements.
• Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
• Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and AWS ‘big data’ technologies.
• Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics.
• Work with stakeholders including the Executive, Product, Data and Design teams to assist with data-related technical issues and support their data infrastructure needs.
• Keep our data separated and secure across national boundaries through multiple data centers and AWS regions.
• Create data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader.
• Work with data and analytics experts to strive for greater functionality in our data systems.

• Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases.
• Experience building and optimizing ‘big data’ data pipelines, architectures and data sets.
• Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
• Strong analytic skills related to working with unstructured datasets.
• Build processes supporting data transformation, data structures, metadata, dependency and workload management.
• A successful history of manipulating, processing and extracting value from large disconnected datasets.
• Working knowledge of message queuing, stream processing, and highly scalable ‘big data’ data stores.
• Strong project management and organizational skills.
• Experience supporting and working with cross-functional teams in a dynamic environment.
• We are looking for a candidate with 5+ years of experience in a Data Engineer role, who has attained a Graduate degree in Computer Science, Statistics, Informatics, Information Systems or another quantitative field. They should also have experience using the following software/tools:

• Experience with big data tools: Hadoop, Spark, Kafka, etc.
• Experience with relational SQL and NoSQL databases, including Postgres and Cassandra.
• Experience with data pipeline and workflow management tools: Azkaban, Luigi, Airflow, etc.
• Experience with AWS cloud services: EC2, EMR, RDS, Redshift
• Experience with stream-processing systems: Storm, Spark-Streaming, etc.
• Experience with object-oriented/object function scripting languages: Python, Java, C++, Scala, etc.

PriceLabs (https://www.chicagobusiness.com/innovators/what-if-you-could-adjust-prices-meet-demand" target="_blank">chicagobusiness.com/innovators/what-if-you-could-adjust-prices-meet-demand) is a cloud based software for vacation and short term rentals to help them dynamically manage prices just the way large hotels and airlines do! Our mission is to help small businesses in the travel and tourism industry by giving them access to advanced analytical systems that are often restricted to large companies. 

We're looking for someone with strong analytical capabilities who wants to understand how our current architecture and algorithms work, and help us design and develop long lasting solutions to address those. Depending on the needs of the day, the role will come with a good mix of team-work, following our best practices, introducing us to industry best practices, independent thinking, and ownership of your work.

 

Responsibilities:

• Design, develop and enhance our pricing algorithms to enable new capabilities.
• Process, analyze, model, and visualize findings from our market level supply and demand data.
• Build and enhance internal and customer facing dashboards to better track metrics and trends that help customers use PriceLabs in a better way.
• Take ownership of product ideas and design discussions.
• Occasional travel to conferences to interact with prospective users and partners, and learn where the industry is headed.

Requirements:

• Bachelors, Masters or Ph. D. in Operations Research, Industrial Engineering, Statistics, Computer Science or other quantitative/engineering fields.
• Strong understanding of analysis of algorithms, data structures and statistics.
• Solid programming experience. Including being able to quickly prototype an idea and test it out.
• Strong communication skills, including the ability and willingness to explain complicated algorithms and concepts in simple terms.
• Experience with relational databases and strong knowledge of SQL.
• Experience building data heavy analytical models in the travel industry.
• Experience in the vacation rental industry.
• Experience developing dynamic pricing models.
• Prior experience working at a fast paced environment.
• Willingness to wear many hats.

1. Create and maintain optimal data pipeline architecture
2. Assemble large, complex data sets that meet business requirements
3. Identify, design, and implement internal process improvements
4. Optimize data delivery and re-design infrastructure for greater scalability
5. Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and AWS technologies
6. Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency, and other key business performance metrics
7. Work with internal and external stakeholders to assist with data-related technical issues and support data infrastructure needs
8. Create data tools for analytics and data scientist team members
 
Skills Required:
 
1. Working knowledge of ETL on any cloud (Azure / AWS / GCP)
2. Proficient in Python (Programming / Scripting)
3. Good understanding of any of the data warehousing concepts (Snowflake / AWS Redshift / Azure Synapse Analytics / Google Big Query / Hive)
4. In-depth understanding of principles of database structure
5.  Good understanding of any of the ETL technologies (Informatica PowerCenter / AWS Glue / Data Factory / SSIS / Spark / Matillion / Talend / Azure)
6. Proficient in SQL (query solving)
7. Knowledge in Change case Management / Version Control – (VSS / DevOps / TFS / GitHub, Bit bucket, CICD Jenkin)

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