1. Expert in deep learning and machine learning techniques,
2. Extremely Good in image/video processing,
3. Have a Good understanding of Linear algebra, Optimization techniques, Statistics and pattern recognition.
Then u r the right fit for this position.
About Yottaasys AI LLC
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Python + Data scientist
at A leading global information technology and business process
Python + Data scientist : |
• Build data-driven models to understand the characteristics of engineering systems |
• Train, tune, validate, and monitor predictive models |
• Sound knowledge on Statistics |
• Experience in developing data processing tasks using PySpark such as reading, merging, enrichment, loading of data from external systems to target data destinations |
• Working knowledge on Big Data or/and Hadoop environments |
• Experience creating CI/CD Pipelines using Jenkins or like tools |
• Practiced in eXtreme Programming (XP) disciplines |
About the role:
Looking for an engineer to apply Deep Learning algorithms to implement and improve perception algorithms related to Autonomous vehicles. The position requires you to work on the full life-cycle of Deep learning development including data collection, feature engineering, model training, and testing. One will have the opportunity to implement a state-of-the-art Deep learning algorithm and apply it to real end-to-end production. You will be working with the team and team lead on challenging Deep Learning projects to deliver product quality improvements.
Responsibilities:
- Build novel architectures for classifying, detecting, and tracking objects.
- Develop efficient Deep Learning architectures that can run in real-time on NVIDIA devices.
- Optimize the stack for deployment on embedded devices
- Work on Data pipeline – Data Acquisition, pre-processing, and analysis.
Skillsets:
- Languages: C++, Python.
- Frameworks: CUDA, TensorRT, Pytorch, Tensorflow, ONNX.
- Good understanding of Linux and Version Control (Git, GitHub, GitLab).
- Experienced with OpenCV, Deep Learning to solve image domain problems.
- Strong understanding of ROS.
- Skilled with software design, development, and bug-fixing.
- Coordinate with team members for the development and maintenance of the package.
- Strong mathematical skills and understanding of probabilistic techniques.
- Experience handling large data sets efficiently.
- Experience with deploying Deep Learning models for real-time applications on Nvidia platforms like Drive AGX Pegasus, Jetson AGX Xavier, etc.
Add On Skills:
- Frameworks: Pytorch Lighting
- Experience with autonomous robots
- OpenCV projects, Deep Learning projects
- Experience with 3D data and representations (point clouds, meshes, etc.)
- Experience with a wide variety of Deep learning Models (e.g: LSTM, RNN, CNN, GAN, etc.)
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.
Carsome’s Data Department is on the lookout for a Data Scientist/Senior Data Scientist who has a strong passion in building data powered products.
Data Science function under the Data Department has a responsibility for standardisation of methods, mentoring team of data science resources/interns, including code libraries and documentation, quality assurance of outputs, modeling techniques and statistics, leveraging a variety of technologies, open-source languages, and cloud computing platform.
You will get to lead & implement projects such as price optimization/prediction, enabling iconic personalization experiences for our customer, inventory optimization etc.
Job Descriptions
- Identifying and integrating datasets that can be leveraged through our product and work closely with data engineering team to develop data products.
- Execute analytical experiments methodically to help solve various problems and make a true impact across functions such as operations, finance, logistics, marketing.
- Identify, prioritize, and design testing opportunities that will inform algorithm enhancements.
- Devise and utilize algorithms and models to mine big data stores, perform data and error analysis to improve models and clean and validate data for uniformity and accuracy.
- Unlock insights by analyzing large amounts of complex website traffic and transactional data.
- Implement analytical models into production by collaborating with data analytics engineers.
Technical Requirements
- Expertise in model design, training, evaluation, and implementation ML Algorithm expertise K-nearest neighbors, Random Forests, Naive Bayes, Regression Models. PyTorch, TensorFlow, Keras, deep learning expertise, tSNE, gradient boosting expertise, regression implementation expertise, Python, Pyspark, SQL, R, AWS Sagemaker /personalize etc.
- Machine Learning / Data Science Certification
Experience & Education
- Bachelor’s in Engineering / Master’s in Data Science / Postgraduate Certificate in Data Science.
- Design, implement and support an analytical data infrastructure, providing ad hoc access to large data sets and computing power.
- Contribute to development of standards and the design and implementation of proactive processes to collect and report data and statistics on assigned systems.
- Research opportunities for data acquisition and new uses for existing data.
- Provide technical development expertise for designing, coding, testing, debugging, documenting and supporting data solutions.
- Experience building data pipelines to connect analytics stacks, client data visualization tools and external data sources.
- Experience with cloud and distributed systems principles
- Experience with Azure/AWS/GCP cloud infrastructure
- Experience with Databricks Clusters and Configuration
- Experience with Python, R, sh/bash and JVM-based languages including Scala and Java.
- Experience with Hadoop family languages including Pig and Hive.
• Total of 4+ years of experience in development, architecting/designing and implementing Software solutions for enterprises.
• Must have strong programming experience in either Python or Java/J2EE.
• Minimum of 4+ year’s experience working with various Cloud platforms preferably Google Cloud Platform.
• Experience in Architecting and Designing solutions leveraging Google Cloud products such as Cloud BigQuery, Cloud DataFlow, Cloud Pub/Sub, Cloud BigTable and Tensorflow will be highly preferred.
• Presentation skills with a high degree of comfort speaking with management and developers
• The ability to work in a fast-paced, work environment
• Excellent communication, listening, and influencing skills
RESPONSIBILITIES:
• Lead teams to implement and deliver software solutions for Enterprises by understanding their requirements.
• Communicate efficiently and document the Architectural/Design decisions to customer stakeholders/subject matter experts.
• Opportunity to learn new products quickly and rapidly comprehend new technical areas – technical/functional and apply detailed and critical thinking to customer solutions.
• Implementing and optimizing cloud solutions for customers.
• Migration of Workloads from on-prem/other public clouds to Google Cloud Platform.
• Provide solutions to team members for complex scenarios.
• Promote good design and programming practices with various teams and subject matter experts.
• Ability to work on any product on the Google cloud platform.
• Must be hands-on and be able to write code as required.
• Ability to lead junior engineers and conduct code reviews
QUALIFICATION:
• Minimum B.Tech/B.E Engineering graduate
Mining large volumes of credit behavior data to generate insights around product holdings and monetization opportunities for cross sell
Use data science to size opportunity and product potential for launch of any new product/pilots
Build propensity models using heuristics and campaign performance to maximize efficiency.
Conduct portfolio analysis and establish key metrics for cross sell partnership
Desired profile/Skills:
2-5 years of experience with a degree in any quantitative discipline such as Engineering, Computer Science, Economics, Statistics or Mathematics
Excellent problem solving and comprehensive analytical skills – ability to structure ambiguous problem statements, perform detailed analysis and derive crisp insights.
Solid experience in using python and SQL
Prior work experience in a financial services space would be highly valued
Location: Bangalore/ Ahmedabad
REQUIREMENT:
- 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.
RESPONSIBILITY:
- 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.
Job Description
We are looking for a data scientist that will help us to 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 in applying data mining techniques, doing statistical analysis, and building high quality prediction systems integrated with our products.
Responsibilities
- Selecting features, building and optimizing classifiers using machine learning techniques
- Data mining using state-of-the-art methods
- Extending company’s data with third party sources of information when needed
- Enhancing data collection procedures to include information that is relevant for building analytic systems
- Processing, cleansing, and verifying the integrity of data used for analysis
- Doing ad-hoc analysis and presenting results in a clear manner
- Creating automated anomaly detection systems and constant tracking of its performance
Skills and Qualifications
- Excellent understanding of machine learning techniques and algorithms, such as Linear regression, SVM, Decision Forests, LSTM, CNN etc.
- Experience with Deep Learning preferred.
- Experience with common data science toolkits, such as R, NumPy, MatLab, etc. Excellence in at least one of these is highly desirable
- Great communication skills
- Proficiency in using query languages such as SQL, Hive, Pig
- Good applied statistics skills, such as statistical testing, regression, etc.
- Good scripting and programming skills
- Data-oriented personality