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InViz is Bangalore Based Startup helping Enterprises simplifying the Search and Discovery experiences for both their end customers as well as their internal users. We use state-of-the-art technologies in Computer Vision, Natural Language Processing, Text Mining, and other ML techniques to extract information/concepts from data of different formats- text, images, videos and make them easily discoverable through simple human-friendly touchpoints.
TSDE - Data
Data Engineer:
- Should have total 3-6 Yrs of experience in Data Engineering.
- Person should have experience in coding data pipeline on GCP.
- Prior experience on Hadoop systems is ideal as candidate may not have total GCP experience.
- Strong on programming languages like Scala, Python, Java.
- Good understanding of various data storage formats and it’s advantages.
- Should have exposure on GCP tools to develop end to end data pipeline for various scenarios (including ingesting data from traditional data bases as well as integration of API based data sources).
- Should have Business mindset to understand data and how it will be used for BI and Analytics purposes.
- Data Engineer Certification preferred
Experience in Working with GCP tools like |
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Store : CloudSQL , Cloud Storage, Cloud Bigtable, Bigquery, Cloud Spanner, Cloud DataStore |
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Ingest : Stackdriver, Pub/Sub, AppEngine, Kubernete Engine, Kafka, DataPrep , Micro services |
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Schedule : Cloud Composer |
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Processing: Cloud Dataproc, Cloud Dataflow, Cloud Dataprep |
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CI/CD - Bitbucket+Jenkinjs / Gitlab |
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Atlassian Suite |
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About Kloud9:
Kloud9 exists with the sole purpose of providing cloud expertise to the retail industry. Our team of cloud architects, engineers and developers help retailers launch a successful cloud initiative so you can quickly realise the benefits of cloud technology. Our standardised, proven cloud adoption methodologies reduce the cloud adoption time and effort so you can directly benefit from lower migration costs.
Kloud9 was founded with the vision of bridging the gap between E-commerce and cloud. The E-commerce of any industry is limiting and poses a huge challenge in terms of the finances spent on physical data structures.
At Kloud9, we know migrating to the cloud is the single most significant technology shift your company faces today. We are your trusted advisors in transformation and are determined to build a deep partnership along the way. Our cloud and retail experts will ease your transition to the cloud.
Our sole focus is to provide cloud expertise to retail industry giving our clients the empowerment that will take their business to the next level. Our team of proficient architects, engineers and developers have been designing, building and implementing solutions for retailers for an average of more than 20 years.
We are a cloud vendor that is both platform and technology independent. Our vendor independence not just provides us with a unique perspective into the cloud market but also ensures that we deliver the cloud solutions available that best meet our clients' requirements.
Responsibilities:
● Studying, transforming, and converting data science prototypes
● Deploying models to production
● Training and retraining models as needed
● Analyzing the ML algorithms that could be used to solve a given problem and ranking them by their respective scores
● Analyzing the errors of the model and designing strategies to overcome them
● Identifying differences in data distribution that could affect model performance in real-world situations
● Performing statistical analysis and using results to improve models
● Supervising the data acquisition process if more data is needed
● Defining data augmentation pipelines
● Defining the pre-processing or feature engineering to be done on a given dataset
● To extend and enrich existing ML frameworks and libraries
● Understanding when the findings can be applied to business decisions
● Documenting machine learning processes
Basic requirements:
● 4+ years of IT experience in which at least 2+ years of relevant experience primarily in converting data science prototypes and deploying models to production
● Proficiency with Python and machine learning libraries such as scikit-learn, matplotlib, seaborn and pandas
● Knowledge of Big Data frameworks like Hadoop, Spark, Pig, Hive, Flume, etc
● Experience in working with ML frameworks like TensorFlow, Keras, OpenCV
● Strong written and verbal communications
● Excellent interpersonal and collaboration skills.
● Expertise in visualizing and manipulating big datasets
● Familiarity with Linux
● Ability to select hardware to run an ML model with the required latency
● Robust data modelling and data architecture skills.
● Advanced degree in Computer Science/Math/Statistics or a related discipline.
● Advanced Math and Statistics skills (linear algebra, calculus, Bayesian statistics, mean, median, variance, etc.)
Nice to have
● Familiarity with Java, and R code writing.
● 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
● Supervising the data acquisition process if more data is needed
● Finding available datasets online that could be used for training
Why Explore a Career at Kloud9:
With job opportunities in prime locations of US, London, Poland and Bengaluru, we help build your career paths in cutting edge technologies of AI, Machine Learning and Data Science. Be part of an inclusive and diverse workforce that's changing the face of retail technology with their creativity and innovative solutions. Our vested interest in our employees translates to deliver the best products and solutions to our customers.
at Merck Group
The Merck Data Engineering Team is responsible for designing, developing, testing, and supporting automated end-to-end data pipelines and applications on Merck’s data management and global analytics platform (Palantir Foundry, Hadoop, AWS and other components).
The Foundry platform comprises multiple different technology stacks, which are hosted on Amazon Web Services (AWS) infrastructure or on-premise Merck’s own data centers. Developing pipelines and applications on Foundry requires:
• Proficiency in SQL / Java / Python (Python required; all 3 not necessary)
• Proficiency in PySpark for distributed computation
• Familiarity with Postgres and ElasticSearch
• Familiarity with HTML, CSS, and JavaScript and basic design/visual competency
• Familiarity with common databases (e.g. JDBC, mySQL, Microsoft SQL). Not all types required
This position will be project based and may work across multiple smaller projects or a single large project utilizing an agile project methodology.
Roles & Responsibilities:
• Develop data pipelines by ingesting various data sources – structured and un-structured – into Palantir Foundry
• Participate in end to end project lifecycle, from requirements analysis to go-live and operations of an application
• Acts as business analyst for developing requirements for Foundry pipelines
• Review code developed by other data engineers and check against platform-specific standards, cross-cutting concerns, coding and configuration standards and functional specification of the pipeline
• Document technical work in a professional and transparent way. Create high quality technical documentation
• Work out the best possible balance between technical feasibility and business requirements (the latter can be quite strict)
• Deploy applications on Foundry platform infrastructure with clearly defined checks
• Implementation of changes and bug fixes via Merck's change management framework and according to system engineering practices (additional training will be provided)
• DevOps project setup following Agile principles (e.g. Scrum)
• Besides working on projects, act as third level support for critical applications; analyze and resolve complex incidents/problems. Debug problems across a full stack of Foundry and code based on Python, Pyspark, and Java
• Work closely with business users, data scientists/analysts to design physical data models
Duties and Responsibilities:
Research and Develop Innovative Use Cases, Solutions and Quantitative Models
Quantitative Models in Video and Image Recognition and Signal Processing for cloudbloom’s
cross-industry business (e.g., Retail, Energy, Industry, Mobility, Smart Life and
Entertainment).
Design, Implement and Demonstrate Proof-of-Concept and Working Proto-types
Provide R&D support to productize research prototypes.
Explore emerging tools, techniques, and technologies, and work with academia for cutting-
edge solutions.
Collaborate with cross-functional teams and eco-system partners for mutual business benefit.
Team Management Skills
Academic Qualification
7+ years of professional hands-on work experience in data science, statistical modelling, data
engineering, and predictive analytics assignments
Mandatory Requirements: Bachelor’s degree with STEM background (Science, Technology,
Engineering and Management) with strong quantitative flavour
Innovative and creative in data analysis, problem solving and presentation of solutions.
Ability to establish effective cross-functional partnerships and relationships at all levels in a
highly collaborative environment
Strong experience in handling multi-national client engagements
Good verbal, writing & presentation skills
Core Expertise
Excellent understanding of basics in mathematics and statistics (such as differential
equations, linear algebra, matrix, combinatorics, probability, Bayesian statistics, eigen
vectors, Markov models, Fourier analysis).
Building data analytics models using Python, ML libraries, Jupyter/Anaconda and Knowledge
database query languages like SQL
Good knowledge of machine learning methods like k-Nearest Neighbors, Naive Bayes, SVM,
Decision Forests.
Strong Math Skills (Multivariable Calculus and Linear Algebra) - understanding the
fundamentals of Multivariable Calculus and Linear Algebra is important as they form the basis
of a lot of predictive performance or algorithm optimization techniques.
Deep learning : CNN, neural Network, RNN, tensorflow, pytorch, computervision,
Large-scale data extraction/mining, data cleansing, diagnostics, preparation for Modeling
Good applied statistical skills, including knowledge of statistical tests, distributions,
regression, maximum likelihood estimators, Multivariate techniques & predictive modeling
cluster analysis, discriminant analysis, CHAID, logistic & multiple regression analysis
Experience with Data Visualization Tools like Tableau, Power BI, Qlik Sense that help to
visually encode data
Excellent Communication Skills – it is incredibly important to describe findings to a technical
and non-technical audience
Capability for continuous learning and knowledge acquisition.
Mentor colleagues for growth and success
Strong Software Engineering Background
Hands-on experience with data science tools
Responsibilities:
* 3+ years of Data Engineering Experience - Design, develop, deliver and maintain data infrastructures.
* SQL Specialist – Strong knowledge and Seasoned experience with SQL Queries
* Languages: Python
* Good communicator, shows initiative, works well with stakeholders.
* Experience working closely with Data Analysts and provide the data they need and guide them on the issues.
* Solid ETL experience and Hadoop/Hive/Pyspark/Presto/ SparkSQL
* Solid communication and articulation skills
* Able to handle stakeholders independently with less interventions of reporting manager.
* Develop strategies to solve problems in logical yet creative ways.
* Create custom reports and presentations accompanied by strong data visualization and storytelling
We would be excited if you have:
* Excellent communication and interpersonal skills
* Ability to meet deadlines and manage project delivery
* Excellent report-writing and presentation skills
* Critical thinking and problem-solving capabilities
- Experience with relational SQL & NoSQL databases including MySQL & MongoDB.
- Familiar with the basic principles of distributed computing and data modeling.
- Experience with distributed data pipeline frameworks like Celery, Apache Airflow, etc.
- Experience with NLP and NER models is a bonus.
- Experience building reusable code and libraries for future use.
- Experience building REST APIs.
Preference for candidates working in tech product companies
scraping , and problem skills
3+ years of experience in deployment, monitoring, tuning, and administration of high concurrency MySQL production databases.
- Solid understanding of writing optimized SQL queries on MySQL databases
- Understanding of AWS, VPC, networking, security groups, IAM, and roles.
- Expertise in scripting in Python or Shell/Powershell
- Must have experience in large scale data migrations
- Excellent communication skills.
at Bridgei2i Analytics Solutions
The person holding this position is responsible for leading the solution development and implementing advanced analytical approaches across a variety of industries in the supply chain domain.
At this position you act as an interface between the delivery team and the supply chain team, effectively understanding the client business and supply chain.
Candidates will be expected to lead projects across several areas such as
- Demand forecasting
- Inventory management
- Simulation & Mathematical optimization models.
- Procurement analytics
- Distribution/Logistics planning
- Network planning and optimization
Qualification and Experience
- 4+ years of analytics experience in supply chain – preferable industries hi-tech, consumer technology, CPG, automobile, retail or e-commerce supply chain.
- Master in Statistics/Economics or MBA or M. Sc./M. Tech with Operations Research/Industrial Engineering/Supply Chain
- Hands-on experience in delivery of projects using statistical modelling
Skills / Knowledge
- Hands on experience in statistical modelling software such as R/ Python and SQL.
- Experience in advanced analytics / Statistical techniques – Regression, Decision tress, Ensemble machine learning algorithms etc. will be considered as an added advantage.
- Highly proficient with Excel, PowerPoint and Word applications.
- APICS-CSCP or PMP certification will be added advantage
- Strong knowledge of supply chain management
- Working knowledge on the linear/nonlinear optimization
- Ability to structure problems through a data driven decision-making process.
- Excellent project management skills, including time and risk management and project structuring.
- Ability to identify and draw on leading-edge analytical tools and techniques to develop creative approaches and new insights to business issues through data analysis.
- Ability to liaison effectively with multiple stakeholders and functional disciplines.
- Experience in Optimization tools like Cplex, ILOG, GAMS will be an added advantage.