About Monexo FinTech (P) Ltd
Monexo is an Reserve Bank of India approved Peer-to-Peer (P2P) Lending marketplace. P2P lending is democratizing finance.
We are driving 'credit inclusion' through paperless onboarding of young working class earning between 15,000 to 30,000 per month with Data Science.
Being a marketplace model - we have lenders who are diversifying beyond Saving Account, Fixed Deposits and Mutual Funds to earn a better yield on their savings.
We are part of the India FinTech industry and invite you to be part of this revolution.
Similar jobs
o You’re both relentless and kind, and don’t see these as being mutually
exclusive
o You have a self-directed learning style, an insatiable curiosity, and a
hands-on execution mindset
o You have deep experience working with product and engineering teams
to launch machine learning products that users love in new or rapidly
evolving markets
o You flourish in uncertain environments and can turn incomplete,
conflicting, or ambiguous inputs into solid data-science action plans
o You bring best practices to feature engineering, model development, and
ML operations
o Your experience in deploying and monitoring the performance of models
in production enables us to implement a best-in-class solution
o You have exceptional writing and speaking skills with a talent for
articulating how data science can be applied to solve customer problems
Must-Have Qualifications
o Graduate degree in engineering, data science, mathematics, physics, or
another quantitative field
o 5+ years of hands-on experience in building and deploying production-
grade ML models with ML frameworks (TensorFlow, Keras, PyTorch) and
libraries like scikit-learn
o Track-record in building ML pipelines for time series, classification, and
predictive applications
o Expert level skills in Python for data analysis and visualization, hypothesis
testing, and model building
o Deep experience with ensemble ML approaches including random forests
and xgboost, and experience with databases and querying models for
structured and unstructured data
o A knack for using data visualization and analysis tools to tell a story
o You naturally think quantitatively about problems and work backward
from a customer outcome
What’ll make you stand out (but not required)
o You have a keen awareness or interest in network analysis/graph analysis
or NLP
o You have experience in distributed systems and graph databases
o You have a strong connection to finance teams or closely related
domains, the challenges they face, and a deep appreciation for their
aspirations
Job Description
Mandatory Requirements
-
Experience in AWS Glue
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Experience in Apache Parquet
-
Proficient in AWS S3 and data lake
-
Knowledge of Snowflake
-
Understanding of file-based ingestion best practices.
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Scripting language - Python & pyspark
CORE RESPONSIBILITIES
-
Create and manage cloud resources in AWS
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Data ingestion from different data sources which exposes data using different technologies, such as: RDBMS, flat files, Streams, and Time series data based on various proprietary systems. Implement data ingestion and processing with the help of Big Data technologies
-
Data processing/transformation using various technologies such as Spark and Cloud Services. You will need to understand your part of business logic and implement it using the language supported by the base data platform
-
Develop automated data quality check to make sure right data enters the platform and verifying the results of the calculations
-
Develop an infrastructure to collect, transform, combine and publish/distribute customer data.
-
Define process improvement opportunities to optimize data collection, insights and displays.
-
Ensure data and results are accessible, scalable, efficient, accurate, complete and flexible
-
Identify and interpret trends and patterns from complex data sets
-
Construct a framework utilizing data visualization tools and techniques to present consolidated analytical and actionable results to relevant stakeholders.
-
Key participant in regular Scrum ceremonies with the agile teams
-
Proficient at developing queries, writing reports and presenting findings
-
Mentor junior members and bring best industry practices.
QUALIFICATIONS
-
5-7+ years’ experience as data engineer in consumer finance or equivalent industry (consumer loans, collections, servicing, optional product, and insurance sales)
-
Strong background in math, statistics, computer science, data science or related discipline
-
Advanced knowledge one of language: Java, Scala, Python, C#
-
Production experience with: HDFS, YARN, Hive, Spark, Kafka, Oozie / Airflow, Amazon Web Services (AWS), Docker / Kubernetes, Snowflake
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Proficient with
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Data mining/programming tools (e.g. SAS, SQL, R, Python)
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Database technologies (e.g. PostgreSQL, Redshift, Snowflake. and Greenplum)
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Data visualization (e.g. Tableau, Looker, MicroStrategy)
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Comfortable learning about and deploying new technologies and tools.
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Organizational skills and the ability to handle multiple projects and priorities simultaneously and meet established deadlines.
-
Good written and oral communication skills and ability to present results to non-technical audiences
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Knowledge of business intelligence and analytical tools, technologies and techniques.
Familiarity and experience in the following is a plus:
-
AWS certification
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Spark Streaming
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Kafka Streaming / Kafka Connect
-
ELK Stack
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Cassandra / MongoDB
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CI/CD: Jenkins, GitLab, Jira, Confluence other related tools
Data Science Engineer
at TartanHQ Solutions Private Limited
Key deliverables for the Data Science Engineer would be to help us discover the information hidden in vast amounts of data, and help us make smarter decisions to deliver even better products. Your primary focus will be on applying data mining techniques, doing statistical analysis, and building high-quality prediction systems integrated with our products.
What will you do?
- You will be building and deploying ML models to solve specific business problems related to NLP, computer vision, and fraud detection.
- You will be constantly assessing and improving the model using techniques like Transfer learning
- You will identify valuable data sources and automate collection processes along with undertaking pre-processing of structured and unstructured data
- You will own the complete ML pipeline - data gathering/labeling, cleaning, storage, modeling, training/testing, and deployment.
- Assessing the effectiveness and accuracy of new data sources and data gathering techniques.
- Building predictive models and machine-learning algorithms to apply to data sets.
- Coordinate with different functional teams to implement models and monitor outcomes.
- Presenting information using data visualization techniques and proposing solutions and strategies to business challenges
We would love to hear from you if :
- You have 2+ years of experience as a software engineer at a SaaS or technology company
- Demonstrable hands-on programming experience with Python/R Data Science Stack
- Ability to design and implement workflows of Linear and Logistic Regression, Ensemble Models (Random Forest, Boosting) using R/Python
- Familiarity with Big Data Platforms (Databricks, Hadoop, Hive), AWS Services (AWS, Sagemaker, IAM, S3, Lambda Functions, Redshift, Elasticsearch)
- Experience in Probability and Statistics, ability to use ideas of Data Distributions, Hypothesis Testing and other Statistical Tests.
- Demonstrable competency in Data Visualisation using the Python/R Data Science Stack.
- Preferable Experience Experienced in web crawling and data scraping
- Strong experience in NLP. Worked on libraries such as NLTK, Spacy, Pattern, Gensim etc.
- Experience with text mining, pattern matching and fuzzy matching
Why Tartan?
- Brand new Macbook
- Stock Options
- Health Insurance
- Unlimited Sick Leaves
- Passion Fund (Invest in yourself or your passion project)
- Wind Down
As a Data Engineer, you are a full-stack data engineer that loves solving business problems.
You work with business leads, analysts and data scientists to understand the business domain
and engage with fellow engineers to build data products that empower better decision making.
You are passionate about data quality of our business metrics and flexibility of your solution that
scales to respond to broader business questions.
If you love to solve problems using your skills, then come join the Team Searce. We have a
casual and fun office environment that actively steers clear of rigid "corporate" culture, focuses
on productivity and creativity, and allows you to be part of a world-class team while still being
yourself.
What You’ll Do
● Understand the business problem and translate these to data services and engineering
outcomes
● Explore new technologies and learn new techniques to solve business problems
creatively
● Think big! and drive the strategy for better data quality for the customers
● Collaborate with many teams - engineering and business, to build better data products
What We’re Looking For
● Over 1-3 years of experience with
○ Hands-on experience of any one programming language (Python, Java, Scala)
○ Understanding of SQL is must
○ Big data (Hadoop, Hive, Yarn, Sqoop)
○ MPP platforms (Spark, Pig, Presto)
○ Data-pipeline & scheduler tool (Ozzie, Airflow, Nifi)
○ Streaming engines (Kafka, Storm, Spark Streaming)
○ Any Relational database or DW experience
○ Any ETL tool experience
● Hands-on experience in pipeline design, ETL and application development
Job Overview
We are looking for a Data Engineer to join our data team to solve data-driven critical
business problems. The hire will be responsible for expanding and optimizing the existing
end-to-end architecture including the data pipeline architecture. The Data Engineer will
collaborate with software developers, database architects, data analysts, data scientists and platform team on data initiatives and will ensure optimal data delivery architecture is
consistent throughout ongoing projects. The right candidate should have hands on in
developing a hybrid set of data-pipelines depending on the business requirements.
Responsibilities
- Develop, construct, test and maintain existing and new data-driven architectures.
- Align architecture with business requirements and provide solutions which fits best
- to solve the business problems.
- Build the infrastructure required for optimal extraction, transformation, and loading
- of data from a wide variety of data sources using SQL and Azure ‘big data’
- technologies.
- Data acquisition from multiple sources across the organization.
- Use programming language and tools efficiently to collate the data.
- Identify ways to improve data reliability, efficiency and quality
- Use data to discover tasks that can be automated.
- Deliver updates to stakeholders based on analytics.
- Set up practices on data reporting and continuous monitoring
Required Technical Skills
- Graduate in Computer Science or in similar quantitative area
- 1+ years of relevant work experience as a Data Engineer or in a similar role.
- Advanced SQL knowledge, Data-Modelling and experience working with relational
- databases, query authoring (SQL) as well as working familiarity with a variety of
- databases.
- Experience in developing and optimizing ETL pipelines, big data pipelines, and datadriven
- architectures.
- Must have strong big-data core knowledge & experience in programming using Spark - Python/Scala
- Experience with orchestrating tool like Airflow or similar
- Experience with Azure Data Factory is good to have
- Build processes supporting data transformation, data structures, metadata,
- dependency and workload management.
- Experience supporting and working with cross-functional teams in a dynamic
- environment.
- Good understanding of Git workflow, Test-case driven development and using CICD
- is good to have
- Good to have some understanding of Delta tables It would be advantage if the candidate also have below mentioned experience using
- the following software/tools:
- Experience with big data tools: Hadoop, Spark, Hive, etc.
- Experience with relational SQL and NoSQL databases
- Experience with cloud data services
- Experience with object-oriented/object function scripting languages: Python, Scala, etc.
Responsibilities
- Understanding the business requirements so as to formulate the problems to solve and restrict the slice of data to be explored.
- Collecting data from various sources.
- Performing cleansing, processing, and validation on the data subject to analyze, in order to ensure its quality.
- Exploring and visualizing data.
- Performing statistical analysis and experiments to derive business insights.
- Clearly communicating the findings from the analysis to turn information into something actionable through reports, dashboards, and/or presentations.
Skills
- Experience solving problems in the project’s business domain.
- Experience with data integration from multiple sources
- Proficiency in at least one query language, especially SQL.
- Working experience with NoSQL databases, such as MongoDB and Elasticsearch.
- Working experience with popular statistical and machine learning techniques, such as clustering, linear regression, KNN, decision trees, etc.
- Good scripting skills using Python, R or any other relevant language
- Proficiency in at least one data visualization tool, such as Matplotlib, Plotly, D3.js, ggplot, etc.
- Great communication skills.
- Gather information from multiple data sources make Approval Decisions mechanically
- Read and interpret credit related information to the borrowers
- Interpret, analyze and assess all forms of complex information
- Embark on risk assessment analysis
- Maintain the credit exposure of the company within certain risk level with set limit in mind
- Build strategies to minimize risk and increase approval rates
- Design Champion and Challenger tests, implement and read test results
- Build Line assignment strategies
- Credit Risk Modeling
- Statistical Data Understanding and interpretation
- Basic Regression and Advanced Machine Learning Models
- Conversant with coding on Python using libraries like Sklearn etc.
- Build and understand decision trees
Job Profile:
As an Applied Scientist, you will be responsible for implementing cutting edge AI/ML algorithms in Computer Vision and Natural Language Processing problems. You need to collaborate with engineers and researchers to critically analyze, provide insights and visualizations for solving complex problems in Ziroh Labs. You will train AI/ML models in Python and often integrate and deploy in Java, C++, C# etc.
Preferred Qualifications:
- Masters in Data Science, AI/ML or quantitative fields like Mathematics, Statistics, Computer Science, Physics, etc.
- Experience with Python, Tensorflow, Keras and Pytorch
- Experience in OpenCV, NLTK, GenSim, spaCy, etc.
- Mathematical understanding of AI/ML algorithms
- Contribution to Open-source projects will have higher chances
Senior Machine Learning Engineer
at AthenasOwl
Company Profile and Job Description
About us:
AthenasOwl (AO) is our “AI for Media” solution that helps content creators and broadcasters to create and curate smarter content. We launched the product in 2017 as an AI-powered suite meant for the media and entertainment industry. Clients use AthenaOwl's context adapted technology for redesigning content, taking better targeting decisions, automating hours of post-production work and monetizing massive content libraries.
For more details visit: www.athenasowl.tv
|
Role: |
Senior Machine Learning Engineer |
|
Experience Level: |
4 -6 Years of experience |
|
Work location: |
Mumbai (Malad W) |
Responsibilities:
- Develop cutting edge machine learning solutions at scale to solve computer vision problems in the domain of media, entertainment and sports
- Collaborate with media houses and broadcasters across the globe to solve niche problems in the field of post-production, archiving and viewership
- Manage a team of highly motivated engineers to deliver high-impact solutions quickly and at scale
The ideal candidate should have:
- Strong programming skills in any one or more programming languages like Python and C/C++
- Sound fundamentals of data structures, algorithms and object-oriented programming
- Hands-on experience with any one popular deep learning framework like TensorFlow, PyTorch, etc.
- Experience in implementing Deep Learning Solutions (Computer Vision, NLP etc.)
- Ability to quickly learn and communicate the latest findings in AI research
- Creative thinking for leveraging machine learning to build end-to-end intelligent software systems
- A pleasantly forceful personality and charismatic communication style
- Someone who will raise the average effectiveness of the team and has demonstrated exceptional abilities in some area of their life. In short, we are looking for a “Difference Maker”
