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Python
Data AnalyticsObject-oriented languages (e.g. Python, PySpark, Java, C#, C++ ) and frameworks (e.g. J2EE or .NET)
Data Engineering : Senior Engineer / Manager
As Senior Engineer/ Manager in Data Engineering, you will translate client requirements into technical design, and implement components for a data engineering solutions. Utilize a deep understanding of data integration and big data design principles in creating custom solutions or implementing package solutions. You will independently drive design discussions to insure the necessary health of the overall solution.
Must Have skills :
1. GCP
2. Spark streaming : Live data streaming experience is desired.
3. Any 1 coding language: Java/Pyhton /Scala
Skills & Experience :
- Overall experience of MINIMUM 5+ years with Minimum 4 years of relevant experience in Big Data technologies
- Hands-on experience with the Hadoop stack - HDFS, sqoop, kafka, Pulsar, NiFi, Spark, Spark Streaming, Flink, Storm, hive, oozie, airflow and other components required in building end to end data pipeline. Working knowledge on real-time data pipelines is added advantage.
- Strong experience in at least of the programming language Java, Scala, Python. Java preferable
- Hands-on working knowledge of NoSQL and MPP data platforms like Hbase, MongoDb, Cassandra, AWS Redshift, Azure SQLDW, GCP BigQuery etc.
- Well-versed and working knowledge with data platform related services on GCP
- Bachelor's degree and year of work experience of 6 to 12 years or any combination of education, training and/or experience that demonstrates the ability to perform the duties of the position
Your Impact :
- Data Ingestion, Integration and Transformation
- Data Storage and Computation Frameworks, Performance Optimizations
- Analytics & Visualizations
- Infrastructure & Cloud Computing
- Data Management Platforms
- Build functionality for data ingestion from multiple heterogeneous sources in batch & real-time
- Build functionality for data analytics, search and aggregation
- Mandatory - Hands on experience in Python and PySpark.
- Build pySpark applications using Spark Dataframes in Python using Jupyter notebook and PyCharm(IDE).
- Worked on optimizing spark jobs that processes huge volumes of data.
- Hands on experience in version control tools like Git.
- Worked on Amazon’s Analytics services like Amazon EMR, Lambda function etc
- Worked on Amazon’s Compute services like Amazon Lambda, Amazon EC2 and Amazon’s Storage service like S3 and few other services like SNS.
- Experience/knowledge of bash/shell scripting will be a plus.
- Experience in working with fixed width, delimited , multi record file formats etc.
- Hands on experience in tools like Jenkins to build, test and deploy the applications
- Awareness of Devops concepts and be able to work in an automated release pipeline environment.
- Excellent debugging skills.
PythonJob Responsibilities
- Design, build & test ETL processes using Python & SQL for the corporate data warehouse
- Inform, influence, support, and execute our product decisions
- Maintain advertising data integrity by working closely with R&D to organize and store data in a format that provides accurate data and allows the business to quickly identify issues.
- Evaluate and prototype new technologies in the area of data processing
- Think quickly, communicate clearly and work collaboratively with product, data, engineering, QA and operations teams
- High energy level, strong team player and good work ethic
- Data analysis, understanding of business requirements and translation into logical pipelines & processes
- Identification, analysis & resolution of production & development bugs
- Support the release process including completing & reviewing documentation
- Configure data mappings & transformations to orchestrate data integration & validation
- Provide subject matter expertise
- Document solutions, tools & processes
- Create & support test plans with hands-on testing
- Peer reviews of work developed by other data engineers within the team
- Establish good working relationships & communication channels with relevant departments
Skills and Qualifications we look for
- University degree 2.1 or higher (or equivalent) in a relevant subject. Master’s degree in any data subject will be a strong advantage.
- 4 - 6 years experience with data engineering.
- Strong coding ability and software development experience in Python.
- Strong hands-on experience with SQL and Data Processing.
- Google cloud platform (Cloud composer, Dataflow, Cloud function, Bigquery, Cloud storage, dataproc)
- Good working experience in any one of the ETL tools (Airflow would be preferable).
- Should possess strong analytical and problem solving skills.
- Good to have skills - Apache pyspark, CircleCI, Terraform
- Motivated, self-directed, able to work with ambiguity and interested in emerging technologies, agile and collaborative processes.
- Understanding & experience of agile / scrum delivery methodology
Data AnalyticsSupporting today’s data driven business world, our client acts as a full-stack data intelligence platform which leverages granular and deep data from various sources, thus helping the decision-makers at the executive level. Their solutions include supply chain optimization, building footprints, track construction hotspots, real estate, and lots more.
Their work embeds geospatial analytics, location intelligence and predictive modelling in the foundations of economic modelling and evaluation theory to build data intelligence layers for their clients which include governments, multilateral institutions, and private organizations.
Headquartered in New Delhi, our client works as a team of economists, data scientists, geo-spatial analysts, etc. Their decision-support system includes Big-Data, predictive modeling, forecasting, socio economic dataset and many more.
As a Senior Manager– Data Intelligence, you will be responsible for contributing to all stages of projects– conceptualizing, preparing work plans, overseeing analytical work, driving teams to meet targets and ensuring quality standards.
What you will do:
- Thoroughly understanding the data processing pipeline and troubleshooting/problem-solving the technical team
- Acting as SPOC for client communications across the portfolio of projects undertaken by the organization
- Contributing to different aspects of organizational growth– team building, process building, strategy and business development
Desired Candidate Profile
What you need to have:- Post-graduate degree in relevant subjects such as Economics/ Engineering/ Quantitative Social Sciences/ Management etc
- At least 5 years of relevant work experience
- Vast experience in managing multiple client projects
- Strong data/quantitative analysis skills are a must
- Prior experience working in data analytics teams
- Credible experience of data platforms & languages in the past
Data AnalyticsWhat you will do:
- Bringing data to life via Historical and Real Time Dashboard like:
2. Transaction behavior analytics
3. User level analytics
4. Propensity models and personalization models, eg whats the best product or offer to drive a sale
5. Emails/ SMS/ AN – analytics models getting data from platforms like Netcore+ Branch+ Internal Tables
6. Other reports that are relevant to know what is working, gaps, etc
- Monitoring key metrics such as commission, gross margin, conversion, customer acquisitions etc
- Using the data models and reports to draw actionable and meaningful insights. Based on the insights helping drive the strategy, optimization opportunities, product improvement and more
- Demonstrating examples where data interpretation led to improvement in core business outcomes like better conversion, better ROI from Ad spends, improvements in product etc.
- Digging into data to identify opportunities or problems and translating them into easy-to-understand way for all key business teams
- Working closely with various business stakeholders: Marketing, Customer Insights, Growth and Product teams
- Ensuring effective and timely delivery of reports and insights that analyze business functions and key operations and performance metrics
What you need to have:
- Minimum 2 years of data analytics and interpretation experience
- Proven experience to show how data analytics shaped strategy, marketing and product. Should have multiple examples of this based on current and past experience
- Strong Data Engineering skills using tools like SQL, Python, Tableau, Power BI, Advanced Excel, PowerQuery etc
- Strong marketing acumen to be able to translate data into marketing outcomes
- Good understanding of Google Analytics, Google AdWords, Facebook Ads, CleverTap and other analytics tools
- Familiarity with data sources like Branch/ Clevertap / Firebase, Big Query, Internal Tables (User/ Click/ Transaction/ Events etc)
Who Are We
A research-oriented company with expertise in computer vision and artificial intelligence, at its core, Orbo is a comprehensive platform of AI-based visual enhancement stack. This way, companies can find a suitable product as per their need where deep learning powered technology can automatically improve their Imagery.
ORBO's solutions are helping BFSI, beauty and personal care digital transformation and Ecommerce image retouching industries in multiple ways.
WHY US
- Join top AI company
- Grow with your best companions
- Continuous pursuit of excellence, equality, respect
- Competitive compensation and benefits
You'll be a part of the core team and will be working directly with the founders in building and iterating upon the core products that make cameras intelligent and images more informative.
To learn more about how we work, please check out
Description:
We are looking for a computer vision engineer to lead our team in developing a factory floor analytics SaaS product. This would be a fast-paced role and the person will get an opportunity to develop an industrial grade solution from concept to deployment.
Responsibilities:
- Research and develop computer vision solutions for industries (BFSI, Beauty and personal care, E-commerce, Defence etc.)
- Lead a team of ML engineers in developing an industrial AI product from scratch
- Setup end-end Deep Learning pipeline for data ingestion, preparation, model training, validation and deployment
- Tune the models to achieve high accuracy rates and minimum latency
- Deploying developed computer vision models on edge devices after optimization to meet customer requirements
Requirements:
- Bachelor’s degree
- Understanding about depth and breadth of computer vision and deep learning algorithms.
- Experience in taking an AI product from scratch to commercial deployment.
- Experience in Image enhancement, object detection, image segmentation, image classification algorithms
- Experience in deployment with OpenVINO, ONNXruntime and TensorRT
- Experience in deploying computer vision solutions on edge devices such as Intel Movidius and Nvidia Jetson
- Experience with any machine/deep learning frameworks like Tensorflow, and PyTorch.
- Proficient understanding of code versioning tools, such as Git
Our perfect candidate is someone that:
- is proactive and an independent problem solver
- is a constant learner. We are a fast growing start-up. We want you to grow with us!
- is a team player and good communicator
What We Offer:
- You will have fun working with a fast-paced team on a product that can impact the business model of E-commerce and BFSI industries. As the team is small, you will easily be able to see a direct impact of what you build on our customers (Trust us - it is extremely fulfilling!)
- You will be in charge of what you build and be an integral part of the product development process
- Technical and financial growth!
Data Science
R ProgrammingPython- 6+ months of proven experience as a Data Scientist or Data Analyst
- Understanding of machine-learning and operations research
- Extensive knowledge of R, SQL and Excel
- Analytical mind and business acumen
- Strong Statistical understanding
- Problem-solving aptitude
- BSc/BA in Computer Science, Engineering or relevant field; graduate degree in Data Science or other quantitative field is preferred
PythonRoles & Responsibilities
- Designing and delivering a best-in-class, highly scalable data governance platform
- Improving processes and applying best practices
- Contribute in all scrum ceremonies; assuming the role of ‘scum master’ on a rotational basis
- Development, management and operation of our infrastructure to ensure it is easy to deploy, scalable, secure and fault-tolerant
- Flexible on working hours as per business needs
Machine Learning (ML)Python
Deep LearningResponsibilities:
- Exploring and visualizing data to gain an understanding of it, then identifying differences in data distribution that could affect performance when deploying the model in the real world.
- Verifying data quality, and/or ensuring it via data cleaning.
- Able to adapt and work fast in producing the output which upgrades the decision making of stakeholders using ML.
- To design and develop Machine Learning systems and schemes.
- To perform statistical analysis and fine-tune models using test results.
- To train and retrain ML systems and models as and when necessary.
- To deploy ML models in production and maintain the cost of cloud infrastructure.
- To develop Machine Learning apps according to client and data scientist requirements.
- To analyze the problem-solving capabilities and use-cases of ML algorithms and rank them by how successful they are in meeting the objective.
Technical Knowledge:
- Worked with real time problems, solved them using ML and deep learning models deployed in real time and should have some awesome projects under his belt to showcase.
- Proficiency in Python and experience with working with Jupyter Framework, Google collab and cloud hosted notebooks such as AWS sagemaker, DataBricks etc.
- Proficiency in working with libraries Sklearn, Tensorflow, Open CV2, Pyspark, Pandas, Numpy and related libraries.
- Expert in visualising and manipulating complex datasets.
- Proficiency in working with visualisation libraries such as seaborn, plotly, matplotlib etc.
- Proficiency in Linear Algebra, statistics and probability required for Machine Learning.
- Proficiency in ML Based algorithms for example, Gradient boosting, stacked Machine learning, classification algorithms and deep learning algorithms. Need to have experience in hypertuning various models and comparing the results of algorithm performance.
- Big data Technologies such as Hadoop stack and Spark.
- Basic use of clouds (VM’s example EC2).
- Brownie points for Kubernetes and Task Queues.
- Strong written and verbal communications.
- Experience working in an Agile environment.
Data ScienceR ProgrammingPython
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