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Proficiency in Linux.
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 pipeline and ETL tools like AWS Glue.
Experience working with AWS cloud services: EC2, S3, RDS, Redshift.
Sigmoid works with a variety of clients from start-ups to fortune 500 companies. We are looking for a detailed oriented self-starter to assist our engineering and analytics teams in various roles as a Software Development Engineer.
This position will be a part of a growing team working towards building world class large scale Big Data architectures. This individual should have a sound understanding of programming principles, experience in programming in Java, Python or similar languages and can expect to
spend a majority of their time coding.
Location - Bengaluru and Hyderabad
Responsibilities:
● Good development practices
○ Hands on coder with good experience in programming languages like Java or
Python.
○ Hands-on experience on the Big Data stack like PySpark, Hbase, Hadoop, Mapreduce and ElasticSearch.
○ Good understanding of programming principles and development practices like checkin policy, unit testing, code deployment
○ Self starter to be able to grasp new concepts and technology and translate them into large scale engineering developments
○ Excellent experience in Application development and support, integration development and data management.
● Align Sigmoid with key Client initiatives
○ Interface daily with customers across leading Fortune 500 companies to understand strategic requirements
● Stay up-to-date on the latest technology to ensure the greatest ROI for customer &Sigmoid
○ Hands on coder with good understanding on enterprise level code
○ Design and implement APIs, abstractions and integration patterns to solve challenging distributed computing problems
○ Experience in defining technical requirements, data extraction, data
transformation, automating jobs, productionizing jobs, and exploring new big data technologies within a Parallel Processing environment
● Culture
○ Must be a strategic thinker with the ability to think unconventional /
out:of:box.
○ Analytical and data driven orientation.
○ Raw intellect, talent and energy are critical.
○ Entrepreneurial and Agile : understands the demands of a private, high growth company.
○ Ability to be both a leader and hands on "doer".
Qualifications: -
- Years of track record of relevant work experience and a computer Science or related technical discipline is required
- Experience with functional and object-oriented programming, Java must.
- hand-On knowledge in Map Reduce, Hadoop, PySpark, Hbase and ElasticSearch.
- Effective communication skills (both written and verbal)
- Ability to collaborate with a diverse set of engineers, data scientists and product managers
- Comfort in a fast-paced start-up environment
Preferred Qualification:
- Technical knowledge in Map Reduce, Hadoop & GCS Stack a plus.
- Experience in agile methodology
- Experience with database modeling and development, data mining and warehousing.
- Experience in architecture and delivery of Enterprise scale applications and capable in developing framework, design patterns etc. Should be able to understand and tackle technical challenges, propose comprehensive solutions and guide junior staff
- Experience working with large, complex data sets from a variety of sources
PythonAWS Glue Developer
Work Experience: 6 to 8 Years
Work Location: Noida, Bangalore, Chennai & Hyderabad
Must Have Skills: AWS Glue, DMS, SQL, Python, PySpark, Data integrations and Data Ops,
Job Reference ID:BT/F21/IND
Job Description:
Design, build and configure applications to meet business process and application requirements.
Responsibilities:
7 years of work experience with ETL, Data Modelling, and Data Architecture Proficient in ETL optimization, designing, coding, and tuning big data processes using Pyspark Extensive experience to build data platforms on AWS using core AWS services Step function, EMR, Lambda, Glue and Athena, Redshift, Postgres, RDS etc and design/develop data engineering solutions. Orchestrate using Airflow.
Technical Experience:
Hands-on experience on developing Data platform and its components Data Lake, cloud Datawarehouse, APIs, Batch and streaming data pipeline Experience with building data pipelines and applications to stream and process large datasets at low latencies.
➢ Enhancements, new development, defect resolution and production support of Big data ETL development using AWS native services.
➢ Create data pipeline architecture by designing and implementing data ingestion solutions.
➢ Integrate data sets using AWS services such as Glue, Lambda functions/ Airflow.
➢ Design and optimize data models on AWS Cloud using AWS data stores such as Redshift, RDS, S3, Athena.
➢ Author ETL processes using Python, Pyspark.
➢ Build Redshift Spectrum direct transformations and data modelling using data in S3.
➢ ETL process monitoring using CloudWatch events.
➢ You will be working in collaboration with other teams. Good communication must.
➢ Must have experience in using AWS services API, AWS CLI and SDK
Professional Attributes:
➢ Experience operating very large data warehouses or data lakes Expert-level skills in writing and optimizing SQL Extensive, real-world experience designing technology components for enterprise solutions and defining solution architectures and reference architectures with a focus on cloud technology.
➢ Must have 6+ years of big data ETL experience using Python, S3, Lambda, Dynamo DB, Athena, Glue in AWS environment.
➢ Expertise in S3, RDS, Redshift, Kinesis, EC2 clusters highly desired.
Qualification:
➢ Degree in Computer Science, Computer Engineering or equivalent.
Salary: Commensurate with experience and demonstrated competence
Data AnalyticsPythonWe are looking for a motivated data analyst with sound experience in handling web/ digital analytics, to join us as part of the Kapiva D2C Business Team. This team is primarily responsible for driving sales and customer engagement on our website. This channel has grown 5x in revenue over the last 12 months and is poised to grow another 5x over the next six. It represents a high-growth, important part of our overall e-commerce growth strategy.
The mandate here is to run an end-to-end sustainable e-commerce business, boost sales through marketing campaigns, and build a cutting edge product (website) that optimizes the customer’s journey as well as increases customer lifetime value.
The Data Analyst will support the business heads by providing data-backed insights in order to drive customer growth, retention and engagement. They will be required to set-up and manage reports, test various hypotheses and coordinate with various stakeholders on a day-to-day basis.
Job Responsibilities:
Strategy and planning:
● Work with the D2C functional leads and support analytics planning on a quarterly/ annual basis
● Identify reports and analytics needed to be conducted on a daily/ weekly/ monthly frequency
● Drive planning for hypothesis-led testing of key metrics across the customer funnel
Analytics:
● Interpret data, analyze results using statistical techniques and provide ongoing reports
● Analyze large amounts of information to discover trends and patterns
● Work with business teams to prioritize business and information needs
● Collaborate with engineering and product development teams to setup data infrastructure as needed
Reporting and communication:
● Prepare reports / presentations to present actionable insights that can drive business objectives
● Setup live dashboards reporting key cross-functional metrics
● Coordinate with various stakeholders to collect useful and required data
● Present findings to business stakeholders to drive action across the organization
● Propose solutions and strategies to business challenges
Requirements sought:
Must haves:
● Bachelor’s/ Masters in Mathematics, Economics, Computer Science, Information Management, Statistics or related field
● High proficiency in MS Excel and SQL
● Knowledge of one or more programming languages like Python/ R. Adept at queries, report writing and presenting findings
● Strong analytical skills with the ability to collect, organize, analyze, and disseminate significant amounts of information with attention to detail and accuracy - working knowledge of statistics and statistical methods
● Ability to work in a highly dynamic environment across cross-functional teams; good at
coordinating with different departments and managing timelines
● Exceptional English written/verbal communication
● A penchant for understanding consumer traits and behavior and a keen eye to detail
Good to have:
● Hands-on experience with one or more web analytics tools like Google Analytics, Mixpanel, Kissmetrics, Heap, Adobe Analytics, etc.
● Experience in using business intelligence tools like Metabase, Tableau, Power BI is a plus
● Experience in developing predictive models and machine learning algorithms
Data Science
Machine Learning (ML)Roles and Responsibilities:
- Design, develop, and maintain the end-to-end MLOps infrastructure from the ground up, leveraging open-source systems across the entire MLOps landscape.
- Creating pipelines for data ingestion, data transformation, building, testing, and deploying machine learning models, as well as monitoring and maintaining the performance of these models in production.
- Managing the MLOps stack, including version control systems, continuous integration and deployment tools, containerization, orchestration, and monitoring systems.
- Ensure that the MLOps stack is scalable, reliable, and secure.
Skills Required:
- 3-6 years of MLOps experience
- Preferably worked in the startup ecosystem
Primary Skills:
- Experience with E2E MLOps systems like ClearML, Kubeflow, MLFlow etc.
- Technical expertise in MLOps: Should have a deep understanding of the MLOps landscape and be able to leverage open-source systems to build scalable, reliable, and secure MLOps infrastructure.
- Programming skills: Proficient in at least one programming language, such as Python, and have experience with data science libraries, such as TensorFlow, PyTorch, or Scikit-learn.
- DevOps experience: Should have experience with DevOps tools and practices, such as Git, Docker, Kubernetes, and Jenkins.
Secondary Skills:
- Version Control Systems (VCS) tools like Git and Subversion
- Containerization technologies like Docker and Kubernetes
- Cloud Platforms like AWS, Azure, and Google Cloud Platform
- Data Preparation and Management tools like Apache Spark, Apache Hadoop, and SQL databases like PostgreSQL and MySQL
- Machine Learning Frameworks like TensorFlow, PyTorch, and Scikit-learn
- Monitoring and Logging tools like Prometheus, Grafana, and Elasticsearch
- Continuous Integration and Continuous Deployment (CI/CD) tools like Jenkins, GitLab CI, and CircleCI
- Explain ability and Interpretability tools like LIME and SHAP
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
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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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Machine Learning (ML)Data SciencePythonKey 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
Python
JavaPython
Scala● Working hand in hand with application developers and data scientists to help build softwares that scales in terms of performance and stability Skills ● 3+ years of experience managing large scale data infrastructure and building data pipelines/ data products. ● Proficient in - Any data engineering technologies and proficient in AWS data engineering technologies is plus. ● Language - python, scala or go ● Experience in working with real time streaming systems Experience in handling millions of events per day Experience in developing and deploying data models on Cloud ● Bachelors/Masters in Computer Science or equivalent experience Ability to learn and use skills in new technologies
PythonData Science
R ProgrammingAbout us
DataWeave provides Retailers and Brands with “Competitive Intelligence as a Service” that enables them to take key decisions that impact their revenue. Powered by AI, we provide easily consumable and actionable competitive intelligence by aggregating and analyzing billions of publicly available data points on the Web to help businesses develop data-driven strategies and make smarter decisions.
Data Science@DataWeave
We the Data Science team at DataWeave (called Semantics internally) build the core machine learning backend and structured domain knowledge needed to deliver insights through our data products. Our underpinnings are: innovation, business awareness, long term thinking, and pushing the envelope. We are a fast paced labs within the org applying the latest research in Computer Vision, Natural Language Processing, and Deep Learning to hard problems in different domains.
How we work?
It's hard to tell what we love more, problems or solutions! Every day, we choose to address some of the hardest data problems that there are. We are in the business of making sense of messy public data on the web. At serious scale!
What do we offer?
● Some of the most challenging research problems in NLP and Computer Vision. Huge text and image
datasets that you can play with!
● Ability to see the impact of your work and the value you're adding to our customers almost immediately.
● Opportunity to work on different problems and explore a wide variety of tools to figure out what really
excites you.
● A culture of openness. Fun work environment. A flat hierarchy. Organization wide visibility. Flexible
working hours.
● Learning opportunities with courses and tech conferences. Mentorship from seniors in the team.
● Last but not the least, competitive salary packages and fast paced growth opportunities.
Who are we looking for?
The ideal candidate is a strong software developer or a researcher with experience building and shipping production grade data science applications at scale. Such a candidate has keen interest in liaising with the business and product teams to understand a business problem, and translate that into a data science problem.
You are also expected to develop capabilities that open up new business productization opportunities.
We are looking for someone with a Master's degree and 1+ years of experience working on problems in NLP or Computer Vision.
If you have 4+ years of relevant experience with a Master's degree (PhD preferred), you will be considered for a senior role.
Key problem areas
● Preprocessing and feature extraction noisy and unstructured data -- both text as well as images.
● Keyphrase extraction, sequence labeling, entity relationship mining from texts in different domains.
● Document clustering, attribute tagging, data normalization, classification, summarization, sentiment
analysis.
● Image based clustering and classification, segmentation, object detection, extracting text from images,
generative models, recommender systems.
● Ensemble approaches for all the above problems using multiple text and image based techniques.
Relevant set of skills
● Have a strong grasp of concepts in computer science, probability and statistics, linear algebra, calculus,
optimization, algorithms and complexity.
● Background in one or more of information retrieval, data mining, statistical techniques, natural language
processing, and computer vision.
● Excellent coding skills on multiple programming languages with experience building production grade
systems. Prior experience with Python is a bonus.
● Experience building and shipping machine learning models that solve real world engineering problems.
Prior experience with deep learning is a bonus.
● Experience building robust clustering and classification models on unstructured data (text, images, etc).
Experience working with Retail domain data is a bonus.
● Ability to process noisy and unstructured data to enrich it and extract meaningful relationships.
● Experience working with a variety of tools and libraries for machine learning and visualization, including
numpy, matplotlib, scikit-learn, Keras, PyTorch, Tensorflow.
● Use the command line like a pro. Be proficient in Git and other essential software development tools.
● Working knowledge of large-scale computational models such as MapReduce and Spark is a bonus.
● Be a self-starter—someone who thrives in fast paced environments with minimal ‘management’.
● It's a huge bonus if you have some personal projects (including open source contributions) that you work
on during your spare time. Show off some of your projects you have hosted on GitHub.
Role and responsibilities
● Understand the business problems we are solving. Build data science capability that align with our product strategy.
● Conduct research. Do experiments. Quickly build throw away prototypes to solve problems pertaining to the Retail domain.
● Build robust clustering and classification models in an iterative manner that can be used in production.
● Constantly think scale, think automation. Measure everything. Optimize proactively.
● Take end to end ownership of the projects you are working on. Work with minimal supervision.
● Help scale our delivery, customer success, and data quality teams with constant algorithmic improvements and automation.
● Take initiatives to build new capabilities. Develop business awareness. Explore productization opportunities.
● Be a tech thought leader. Add passion and vibrance to the team. Push the envelope. Be a mentor to junior members of the team.
● Stay on top of latest research in deep learning, NLP, Computer Vision, and other relevant areas.
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