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B2B - Factory app for retailers & buyers (well funded)
Job Title
Data Analyst
Job Brief
The successful candidate will turn data into information, information into insight and insight into business decisions.
Data Analyst Job Duties
Data analyst responsibilities include conducting full lifecycle analysis to include requirements, activities and design. Data analysts will develop analysis and reporting capabilities. They will also monitor performance and quality control plans to identify improvements.
Responsibilities
● Interpret data, analyze results using statistical techniques and provide ongoing reports.
● Develop and implement databases, data collection systems, data analytics and other strategies that optimize statistical efficiency and quality.
● Acquire data fromprimary orsecondary data sources andmaintain databases/data systems.
● Identify, analyze, and interpret trends orpatternsin complex data sets.
● Filter and “clean” data by reviewing computerreports, printouts, and performance indicatorsto locate and correct code problems.
● Work withmanagementto prioritize business and information needs.
● Locate and define new processimprovement opportunities.
Requirements
● Proven working experienceas aData Analyst or BusinessDataAnalyst.
● Technical expertise regarding data models, database design development, data mining and segmentation techniques.
● Strong knowledge of and experience with reporting packages (Business Objects etc), databases (SQL etc), programming (XML, Javascript, or ETL frameworks).
● Knowledge of statistics and experience using statistical packages for analyzing datasets (Excel, SPSS, SAS etc).
● Strong analytical skills with the ability to collect, organize, analyze, and disseminate significant amounts of information with attention to detail and accuracy.
● Adept atqueries,reportwriting and presenting findings.
Job Location SouthDelhi, New Delhi
🚀 Exciting Opportunity: Data Engineer Position in Gurugram 🌐
Hello
We are actively seeking a talented and experienced Data Engineer to join our dynamic team at Reality Motivational Venture in Gurugram (Gurgaon). If you're passionate about data, thrive in a collaborative environment, and possess the skills we're looking for, we want to hear from you!
Position: Data Engineer
Location: Gurugram (Gurgaon)
Experience: 5+ years
Key Skills:
- Python
- Spark, Pyspark
- Data Governance
- Cloud (AWS/Azure/GCP)
Main Responsibilities:
- Define and set up analytics environments for "Big Data" applications in collaboration with domain experts.
- Implement ETL processes for telemetry-based and stationary test data.
- Support in defining data governance, including data lifecycle management.
- Develop large-scale data processing engines and real-time search and analytics based on time series data.
- Ensure technical, methodological, and quality aspects.
- Support CI/CD processes.
- Foster know-how development and transfer, continuous improvement of leading technologies within Data Engineering.
- Collaborate with solution architects on the development of complex on-premise, hybrid, and cloud solution architectures.
Qualification Requirements:
- BSc, MSc, MEng, or PhD in Computer Science, Informatics/Telematics, Mathematics/Statistics, or a comparable engineering degree.
- Proficiency in Python and the PyData stack (Pandas/Numpy).
- Experience in high-level programming languages (C#/C++/Java).
- Familiarity with scalable processing environments like Dask (or Spark).
- Proficient in Linux and scripting languages (Bash Scripts).
- Experience in containerization and orchestration of containerized services (Kubernetes).
- Education in database technologies (SQL/OLAP and Non-SQL).
- Interest in Big Data storage technologies (Elastic, ClickHouse).
- Familiarity with Cloud technologies (Azure, AWS, GCP).
- Fluent English communication skills (speaking and writing).
- Ability to work constructively with a global team.
- Willingness to travel for business trips during development projects.
Preferable:
- Working knowledge of vehicle architectures, communication, and components.
- Experience in additional programming languages (C#/C++/Java, R, Scala, MATLAB).
- Experience in time-series processing.
How to Apply:
Interested candidates, please share your updated CV/resume with me.
Thank you for considering this exciting opportunity.
AWS 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
Responsibilities:
- Designing and implementing fine-tuned production ready data/ML pipelines in Hadoop platform.
- Driving optimization, testing and tooling to improve quality.
- Reviewing and approving high level & amp; detailed design to ensure that the solution delivers to the business needs and aligns to the data & analytics architecture principles and roadmap.
- Understanding business requirements and solution design to develop and implement solutions that adhere to big data architectural guidelines and address business requirements.
- Following proper SDLC (Code review, sprint process).
- Identifying, designing, and implementing internal process improvements: automating manual processes, optimizing data delivery, etc.
- Building robust and scalable data infrastructure (both batch processing and real-time) to support needs from internal and external users.
- Understanding various data security standards and using secure data security tools to apply and adhere to the required data controls for user access in the Hadoop platform.
- Supporting and contributing to development guidelines and standards for data ingestion.
- Working with a data scientist and business analytics team to assist in data ingestion and data related technical issues.
- Designing and documenting the development & deployment flow.
Requirements:
- Experience in developing rest API services using one of the Scala frameworks.
- Ability to troubleshoot and optimize complex queries on the Spark platform
- Expert in building and optimizing ‘big data’ data/ML pipelines, architectures and data sets.
- Knowledge in modelling unstructured to structured data design.
- Experience in Big Data access and storage techniques.
- Experience in doing cost estimation based on the design and development.
- Excellent debugging skills for the technical stack mentioned above which even includes analyzing server logs and application logs.
- Highly organized, self-motivated, proactive, and ability to propose best design solutions.
- Good time management and multitasking skills to work to deadlines by working independently and as a part of a team.
Job Title: Data Engineer
Job Summary: As a Data Engineer, you will be responsible for designing, building, and maintaining the infrastructure and tools necessary for data collection, storage, processing, and analysis. You will work closely with data scientists and analysts to ensure that data is available, accessible, and in a format that can be easily consumed for business insights.
Responsibilities:
- Design, build, and maintain data pipelines to collect, store, and process data from various sources.
- Create and manage data warehousing and data lake solutions.
- Develop and maintain data processing and data integration tools.
- Collaborate with data scientists and analysts to design and implement data models and algorithms for data analysis.
- Optimize and scale existing data infrastructure to ensure it meets the needs of the business.
- Ensure data quality and integrity across all data sources.
- Develop and implement best practices for data governance, security, and privacy.
- Monitor data pipeline performance / Errors and troubleshoot issues as needed.
- Stay up-to-date with emerging data technologies and best practices.
Requirements:
Bachelor's degree in Computer Science, Information Systems, or a related field.
Experience with ETL tools like Matillion,SSIS,Informatica
Experience with SQL and relational databases such as SQL server, MySQL, PostgreSQL, or Oracle.
Experience in writing complex SQL queries
Strong programming skills in languages such as Python, Java, or Scala.
Experience with data modeling, data warehousing, and data integration.
Strong problem-solving skills and ability to work independently.
Excellent communication and collaboration skills.
Familiarity with big data technologies such as Hadoop, Spark, or Kafka.
Familiarity with data warehouse/Data lake technologies like Snowflake or Databricks
Familiarity with cloud computing platforms such as AWS, Azure, or GCP.
Familiarity with Reporting tools
Teamwork/ growth contribution
- Helping the team in taking the Interviews and identifying right candidates
- Adhering to timelines
- Intime status communication and upfront communication of any risks
- Tech, train, share knowledge with peers.
- Good Communication skills
- Proven abilities to take initiative and be innovative
- Analytical mind with a problem-solving aptitude
Good to have :
Master's degree in Computer Science, Information Systems, or a related field.
Experience with NoSQL databases such as MongoDB or Cassandra.
Familiarity with data visualization and business intelligence tools such as Tableau or Power BI.
Knowledge of machine learning and statistical modeling techniques.
If you are passionate about data and want to work with a dynamic team of data scientists and analysts, we encourage you to apply for this position.
GCP Data Analyst profile must have below skills sets :
- Knowledge of programming languages like https://apc01.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.simplilearn.com%2Ftutorials%2Fsql-tutorial%2Fhow-to-become-sql-developer&data=05%7C01%7Ca_anjali%40hcl.com%7C4ae720b3f3cc45c3e04608da3346b335%7C189de737c93a4f5a8b686f4ca9941912%7C0%7C0%7C637878675987971859%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C&sdata=EImfaJAD1KHOyrBQ7FkbaPl1STtfnf4QdQlbjw72%2BmE%3D&reserved=0" target="_blank">SQL, Oracle, R, MATLAB, Java and https://apc01.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.simplilearn.com%2Fwhy-learn-python-a-guide-to-unlock-your-python-career-article&data=05%7C01%7Ca_anjali%40hcl.com%7C4ae720b3f3cc45c3e04608da3346b335%7C189de737c93a4f5a8b686f4ca9941912%7C0%7C0%7C637878675987971859%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C&sdata=Z2n1Xy%2F3YN6nQqSweU5T7EfUTa1kPAAjbCMTWxDCh%2FY%3D&reserved=0" target="_blank">Python
- Data cleansing, data visualization, data wrangling
- Data modeling , data warehouse concepts
- Adapt to Big data platform like Hadoop, Spark for stream & batch processing
- GCP (Cloud Dataproc, Cloud Dataflow, Cloud Datalab, Cloud Dataprep, BigQuery, Cloud Datastore, Cloud Datafusion, Auto ML etc)
Job Description
Lead Machine Learning (ML)/
NLP Engineer
5 + years of experience
About Contify
Contify is an AI-enabled Market and Competitive Intelligence (MCI)
software to help professionals make informed decisions. Its B2B SaaS
platform helps leading organizations such as Ericsson, EY, Wipro,
Deloitte, L&T, BCG, MetLife, etc. track information on their competitors,
customers, industries, and topics of interest by continuously monitoring
over 500,000+ sources on a real-time basis. Contify is rapidly growing
with 185+ people across two offices in India. Contify is the winner of
Frost and Sullivan’s Product Innovation Award for Market and
Competitive Intelligence Platforms.
The role
We are looking for a hardworking, aspirational, and innovative
engineering person for the Lead ML/ NLP Engineer position. You’ll build
Contify’s ML and NLP capabilities and help us extract value from
unstructured data. Using advanced NLP, ML, and text analytics, you will
develop applications that will extract business insights by analyzing a
large amount of unstructured text information, identifying patterns, and
by connecting the events.
Responsibilities:
You will be responsible for all the processes from data collection, and
pre-processing, to training models and deploying them to production.
➔ Understand the business objectives; design and deploy scalable
ML models/ NLP applications to meet those objectives
➔ Use of NLP techniques for text representation, semantic analysis,
information extraction, to meet the business objectives in an
efficient manner along with metrics to measure progress
➔ Extend existing ML libraries and frameworks and use effective text
representations to transform natural language into useful features
➔ Defining and supervising the data collection process, verifying data
quality, and employing data augmentation techniques
➔ Defining the preprocessing or feature engineering to be done on a
given dataset
➔ Analyze the errors of the model and design strategies to overcome
them
➔ Research and implement the right algorithms and tools for ML/
NLP tasks
➔ Collaborate with engineering and product development teams
➔ Represent Contify in external ML industry events and publish
thought leadership articles
Desired Skills and Experience
To succeed in this role, you should possess outstanding skills in
statistical analysis, machine learning methods, and text representation
techniques.
➔ Deep understanding of text representation techniques (such as n-
grams, bag of words, sentiment analysis, etc), statistics and
classification algorithms
➔ Hand on experience in feature extraction techniques for text
classification and topic mining
➔ Knowledge of text analytics with a strong understanding of NLP
algorithms and models (GLMs, SVM, PCA, NB, Clustering, DTs)
and their underlying computational and probabilistic statistics
◆ Word Embedding like Tfidf, Word2Vec, GLove, FastText, etc.
◆ Language models like Bert, GPT, RoBERTa, XLNet
◆ Neural networks like RNN, GRU, LSTM, Bi-LSTM
◆ Classification algorithms like LinearSVC, SVM, LR
◆ XGB, MultinomialNB, etc.
◆ Other Algos- PCA, Clustering methods, etc
➔ Excellent knowledge and demonstrable experience in using NLP
packages such as NLTK, Word2Vec, SpaCy, Gensim, Standford
CoreNLP, TensorFlow/ PyTorch.
➔ Experience in setting up supervised & unsupervised learning
models including data cleaning, data analytics, feature creation,
model selection & ensemble methods, performance metrics &
visualization
➔ Evaluation Metrics- Root Mean Squared Error, Confusion Matrix, F
Score, AUC – ROC, etc
➔ Understanding of knowledge graph will be a plus
Qualifications
➔ Education: Bachelors or Masters in Computer Science,
Mathematics, Computational Linguistics or similar field
➔ At least 4 years' experience building Machine Learning & NLP
solutions over open-source platforms such as SciKit-Learn,
Tensorflow, SparkML, etc
➔ At least 2 years' experience in designing and developing
enterprise-scale NLP solutions in one or more of: Named Entity
Recognition, Document Classification, Feature Extraction, Triplet
Extraction, Clustering, Summarization, Topic Modelling, Dialog
Systems, Sentiment Analysis
➔ Self-starter who can see the big picture, and prioritize your work to
make the largest impact on the business’ and customer’s vision
and requirements
➔ Being a committer or a contributor to an open-source project is a
plus
Note
Contify is a people-oriented company. Emotional intelligence, therefore,
is a must. You should enjoy working in a team environment, supporting
your teammates in pursuit of our common goals, and working with your
colleagues to drive customer value. You strive to not only improve
yourself, but also those around you.
along with metrics to track their progress
Managing available resources such as hardware, data, and personnel so that deadlines
are met
Analysing the ML algorithms that could be used to solve a given problem and ranking
them by their success probability
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
Defining validation strategies
Defining the pre-processing or feature engineering to be done on a given dataset
Defining data augmentation pipelines
Training models and tuning their hyper parameters
Analysing the errors of the model and designing strategies to overcome them
Deploying models to production