Python
Machine Learning (ML)Role: Principal Software Engineer
We looking for a passionate Principle Engineer - Analytics to build data products that extract valuable business insights for efficiency and customer experience. This role will require managing, processing and analyzing large amounts of raw information and in scalable databases. This will also involve developing unique data structures and writing algorithms for the entirely new set of products. The candidate will be required to have critical thinking and problem-solving skills. The candidates must be experienced with software development with advanced algorithms and must be able to handle large volume of data. Exposure with statistics and machine learning algorithms is a big plus. The candidate should have some exposure to cloud environment, continuous integration and agile scrum processes.
Responsibilities:
• Lead projects both as a principal investigator and project manager, responsible for meeting project requirements on schedule
• Software Development that creates data driven intelligence in the products which deals with Big Data backends
• Exploratory analysis of the data to be able to come up with efficient data structures and algorithms for given requirements
• The system may or may not involve machine learning models and pipelines but will require advanced algorithm development
• Managing, data in large scale data stores (such as NoSQL DBs, time series DBs, Geospatial DBs etc.)
• Creating metrics and evaluation of algorithm for better accuracy and recall
• Ensuring efficient access and usage of data through the means of indexing, clustering etc.
• Collaborate with engineering and product development teams.
Requirements:
• Master’s or Bachelor’s degree in Engineering in one of these domains - Computer Science, Information Technology, Information Systems, or related field from top-tier school
• OR Master’s degree or higher in Statistics, Mathematics, with hands on background in software development.
• Experience of 8 to 10 year with product development, having done algorithmic work
• 5+ years of experience working with large data sets or do large scale quantitative analysis
• Understanding of SaaS based products and services.
• Strong algorithmic problem-solving skills
• Able to mentor and manage team and take responsibilities of team deadline.
Skill set required:
• In depth Knowledge Python programming languages
• Understanding of software architecture and software design
• Must have fully managed a project with a team
• Having worked with Agile project management practices
• Experience with data processing analytics and visualization tools in Python (such as pandas, matplotlib, Scipy, etc.)
• Strong understanding of SQL and querying to NoSQL database (eg. Mongo, Casandra, Redis
Subodh Popalwar
Software Engineer, Memorres
About Product Base Company into Logistic
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Who We Are:
DeepIntent is leading the healthcare advertising industry with data-driven solutions built for the future. From day one, our mission has been to improve patient outcomes through the artful use of advertising, data science, and real-world clinical data.
What You’ll Do:
We are looking for a Senior Software Engineer based in Pune, India who can master both DeepIntent’s data architectures and pharma research and analytics methodologies to make significant contributions to how health media is analyzed by our clients. This role requires an Engineer who not only understands DBA functions but also how they impact research objectives and can work with researchers and data scientists to achieve impactful results.
This role will be in the Analytics Organization and will require integration and partnership with the Engineering Organization. The ideal candidate is a self-starter who is inquisitive who is not afraid to take on and learn from challenges and will constantly seek to improve the facets of the business they manage. The ideal candidate will also need to demonstrate the ability to collaborate and partner with others.
- Serve as the Engineering interface between Analytics and Engineering teams
- Develop and standardized all interface points for analysts to retrieve and analyze data with a focus on research methodologies and data based decisioning
- Optimize queries and data access efficiencies, serve as expert in how to most efficiently attain desired data points
- Build “mastered” versions of the data for Analytics specific querying use cases
- Help with data ETL, table performance optimization
- Establish formal data practice for the Analytics practice in conjunction with rest of DeepIntent
- Build & operate scalable and robust data architectures
- Interpret analytics methodology requirements and apply to data architecture to create standardized queries and operations for use by analytics teams
- Implement DataOps practices
- Master existing and new Data Pipelines and develop appropriate queries to meet analytics specific objectives
- Collaborate with various business stakeholders, software engineers, machine learning engineers, analysts
- Operate between Engineers and Analysts to unify both practices for analytics insight creation
Who You Are:
- Adept in market research methodologies and using data to deliver representative insights
- Inquisitive, curious, understands how to query complicated data sets, move and combine data between databases
- Deep SQL experience is a must
- Exceptional communication skills with ability to collaborate and translate with between technical and non technical needs
- English Language Fluency and proven success working with teams in the U.S.
- Experience in designing, developing and operating configurable Data pipelines serving high volume and velocity data
- Experience working with public clouds like GCP/AWS
- Good understanding of software engineering, DataOps, and data architecture, Agile and DevOps methodologies
- Experience building Data architectures that optimize performance and cost, whether the components are prepackaged or homegrown
- Proficient with SQL,Python or JVM based language, Bash
- Experience with any of Apache open source projects such as Spark, Druid, Beam, Airflow etc.and big data databases like BigQuery, Clickhouse, etc
- Ability to think big, take bets and innovate, dive deep, hire and develop the best talent, learn and be curious
- Comfortable to work in EST Time Zone
PythonGood experience in the Extraction, Transformation, and Loading (ETL) of data from various sources into Data Warehouses and Data Marts using Informatica Power Center (Repository Manager,
Designer, Workflow Manager, Workflow Monitor, Metadata Manager), Power Connect as ETL tool on Oracle, and SQL Server Databases.
Knowledge of Data Warehouse/Data mart, ODS, OLTP, and OLAP implementations teamed with
project scope, Analysis, requirements gathering, data modeling, ETL Design, development,
System testing, Implementation, and production support.
Strong experience in Dimensional Modeling using Star and Snow Flake Schema, Identifying Facts
and Dimensions
Used various transformations like Filter, Expression, Sequence Generator, Update Strategy,
Joiner, Stored Procedure, and Union to develop robust mappings in the Informatica Designer.
Developed mapping parameters and variables to support SQL override.
Created applets to use them in different mappings.
Created sessions, configured workflows to extract data from various sources, transformed data,
and loading into the data warehouse.
Used Type 1 SCD and Type 2 SCD mappings to update slowly Changing Dimension Tables.
Modified existing mappings for enhancements of new business requirements.
Involved in Performance tuning at source, target, mappings, sessions, and system levels.
Prepared migration document to move the mappings from development to testing and then to
production repositories
Extensive experience in developing Stored Procedures, Functions, Views and Triggers, Complex
SQL queries using PL/SQL.
Experience in resolving on-going maintenance issues and bug fixes; monitoring Informatica
/Talend sessions as well as performance tuning of mappings and sessions.
Experience in all phases of Data warehouse development from requirements gathering for the
data warehouse to develop the code, Unit Testing, and Documenting.
Extensive experience in writing UNIX shell scripts and automation of the ETL processes using
UNIX shell scripting.
Experience in using Automation Scheduling tools like Control-M.
Hands-on experience across all stages of Software Development Life Cycle (SDLC) including
business requirement analysis, data mapping, build, unit testing, systems integration, and user
acceptance testing.
Build, operate, monitor, and troubleshoot Hadoop infrastructure.
Develop tools and libraries, and maintain processes for other engineers to access data and write
MapReduce programs.
Machine Learning (ML)Python
Deep Learninggeneration.
o 3+ years of software engineering experience.
o Advanced knowledge of Python, with 2+ years in a production environment.
o Experience with practical applications of deep learning.
o Experience with agile, test-driven development, continuous integration, and automated testing.
o Experience with productionizing machine learning models and integrating into web- services.
o Experience with the full software development life cycle, including requirements collection, design, implementation, testing, and operational support.
o Excellent verbal and written communication, teamwork, decision making and influencing
skills.
o Hustle. Thrives in an evolving, fast paced, ambiguous work environment.
Machine Learning (ML)Experience 3 to 8 Years
Skill Set
- experience in algorithm development with a focus on signal processing, pattern recognition, machine learning, classification, data mining, and other areas of machine intelligence.
- Ability to analyse data streams from multiple sensors and develop algorithms to extract accurate and meaningful sport metrics.
- Should have a deeper understanding of IMU sensors and Biosensors like HRM, ECG
- A good understanding on Power and memory management on embedded platform
- Expertise in the design of multitasking, event-driven, real-time firmware using C and understanding of RTOS concepts
- Knowledge of Machine learning, Analytical and methodical approaches to data analysis and verification and Python
- Prior experience on fitness algorithm development using IMU sensor
- Interest in fitness activities and knowledge of human body anatomy
JavaThe thrill of working at a start-up that is starting to scale massively is something else. Simpl (FinTech startup of the year - 2020) was formed in 2015 by Nitya Sharma, an investment banker from Wall Street and Chaitra Chidanand, a tech executive from the Valley, when they teamed up with a very clear mission - to make money simple so that people can live well and do amazing things. Simpl is the payment platform for the mobile-first world, and we’re backed by some of the best names in fintech globally (folks who have invested in Visa, Square and Transferwise), and
has Joe Saunders, Ex Chairman and CEO of Visa as a board member.
Everyone at Simpl is an internal entrepreneur who is given a lot of bandwidth and resources to create the next breakthrough towards the long term vision of “making money Simpl”. Our first product is a payment platform that lets people buy instantly, anywhere online, and pay later. In
the background, Simpl uses big data for credit underwriting, risk and fraud modelling, all without any paperwork, and enables Banks and Non-Bank Financial Companies to access a whole new consumer market.
In place of traditional forms of identification and authentication, Simpl integrates deeply into merchant apps via SDKs and APIs. This allows for more sophisticated forms of authentication that take full advantage of smartphone data and processing power
Skillset:
Workflow manager/scheduler like Airflow, Luigi, Oozie
Good handle on Python
ETL Experience
Batch processing frameworks like Spark, MR/PIG
File formats: parquet, JSON, XML, thrift, avro, protobuff
Rule engine (drools - business rule management system)
Distributed file systems like HDFS, NFS, AWS, S3 and equivalent
Built/configured dashboards
Nice to have:
Data platform experience for eg: building data lakes, working with near - realtime
applications/frameworks like storm, flink, spark.
AWS
File encoding types: Thrift, Avro, Protobuff, Parquet, JSON, XML
HIVE, HBASE
Machine Learning (ML)Deep LearningWe have an Excellent job Opportunity for "Applied Machine Learning Engineer" with one of thr Product based organization for Remote Working Mode or for Mumbai Location.
Job Responsibilities:
- Apply your knowledge of ML and statistics to conceptualise, experiment, develop & deploy machine learning & deep learning systems.
- Understanding the business objectives & defining the right target metrics to track performance & progress.
- Defining & building datasets with the appropriate representation techniques for learning.
- Training & tuning models. Running evaluation & test experiments on the models.
- Build ML pipelines end to end. (Everything MLOps.)
- Building pipelines for the various stages.
- Deploying models.
- Troubleshooting issues with models in production.
- Reporting results of model performance in production.
- Retraining, performance logging & maintenance.
- Help the business with insights for better decision-making. You will build many predictive models for internal business operations
you will derive insights from the trained models & data to help the product & business teams make better decisions.
Requirements:
- 2+ years of work experience as an ML engineer or Data Scientist with a Bachelors Degree in Computer science or related field
- Theoretical & practical knowledge of Machine Learning, Deep Learning and Statistical methods. (NLP Tasks, Recommender Systems, Predictive Modelling etc)
- Since Pepper is a content company, you will work on many interesting text based problems. Solid understanding of Natural Language Processing techniques with Deep Learning is a must for this role.
- Familiarity with the popular NLP applications and text representation architectures & techniques: text classification, machine translation, named entity recognition, summarisation, question answering, zero-shot learning etc. Bag of Words, TF-IDF, Word2vec, GloVe, BERT, ELMo, GPT etc.
- Experience with ML frameworks (like Tensorflow, Keras, PyTorch) & libraries like Sklearn.
- Experience with ML infrastructure & shipping models.
- Excellent programming & algorithmic skills. Good understanding of Data Structures and algorithms (fluent in at least one object oriented programming language). Proficiency in Python is a must.
- Strong understanding of database systems & schema design. Proficient in SQL
Please let us know if you are interested in the above opening and if interested please let us know your
Current CTC :
Expected CTC :
Notice Period :
Relevant experience in Machine Learning :
Relevant experience in Deep Learning:
Relevant experience in NLP Applications:
Regards
Ashwini
- Proficiency in shell scripting
- Proficiency in automation of tasks
- Proficiency in Pyspark/Python
- Proficiency in writing and understanding of sqoop
- Understanding of CloudEra manager
- Good understanding of RDBMS
- Good understanding of Excel
Python- Building and operationalizing large scale enterprise data solutions and applications using one or more of AZURE data and analytics services in combination with custom solutions - Azure Synapse/Azure SQL DWH, Azure Data Lake, Azure Blob Storage, Spark, HDInsights, Databricks, CosmosDB, EventHub/IOTHub.
- Experience in migrating on-premise data warehouses to data platforms on AZURE cloud.
- Designing and implementing data engineering, ingestion, and transformation functions
-
Azure Synapse or Azure SQL data warehouse
-
Spark on Azure is available in HD insights and data bricks
Machine Learning (ML)Responsibilities:
- Develop REST/JSON API’s Design code for high scale/availability/resiliency.
- Develop responsive web apps and integrate APIs using NodeJS.
- Presenting Chat efficiency reports to higher Management
- Develop system flow diagrams to automate a business function and identify impacted systems; metrics to depict the cost benefit analysis of the solutions developed.
- Work closely with business operations to convert requirements into system solutions and collaborate with development teams to ensure delivery of highly scalable and available systems.
- Using tools to classify/categorize the chat based on intents and coming up with F1 score for Chat Analysis
- Experience in analyzing real agents Chat conversation with agent to train the Chatbot.
- Developing Conversational Flows in the chatbot
- Calculating Chat efficiency reports.
Good to Have:
- Monitors performance and quality control plans to identify performance.
- Works on problems of moderate and varied complexity where analysis of data may require adaptation of standardized practices.
- Works with management to prioritize business and information needs.
- Experience in analyzing real agents Chat conversation with agent to train the Chatbot.
- Identifies, analyzes, and interprets trends or patterns in complex data sets.
- Ability to manage multiple assignments.
- Understanding of ChatBot Architecture.
- Experience of Chatbot training
Machine Learning (ML)Python
Data ScienceDeep LearningDataWeave 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 6+ years of relevant experience working on problems in NLP or Computer Vision with a Master's degree (PhD preferred).
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.
Follow CutshortSubodh Popalwar
Software Engineer, Memorres