Job Description
This requirement is to service our client which is a leading big data technology company that measures what viewers consume across platforms to enable marketers make better advertising decisions. We are seeking a Senior Data Operations Analyst to mine large-scale datasets for our client. Their work will have a direct impact on driving business strategies for prominent industry leaders. Self-motivation and strong communication skills are both must-haves. Ability to work in a fast-paced work environment is desired.
Problems being solved by our client:
Measure consumer usage of devices linked to the internet and home networks including computers, mobile phones, tablets, streaming sticks, smart TVs, thermostats and other appliances. There are more screens and other connected devices in homes than ever before, yet there have been major gaps in understanding how consumers interact with this technology. Our client uses a measurement technology to unravel dynamics of consumers’ interactions with multiple devices.
Duties and responsibilities:
- The successful candidate will contribute to the development of novel audience measurement and demographic inference solutions.
- Develop, implement, and support statistical or machine learning methodologies and processes.
- Build, test new features and concepts and integrate into production process
- Participate in ongoing research and evaluation of new technologies
- Exercise your experience in the development lifecycle through analysis, design, development, testing and deployment of this system
- Collaborate with teams in Software Engineering, Operations, and Product Management to deliver timely and quality data. You will be the knowledge expert, delivering quality data to our clients
Qualifications:
- 3-5 years relevant work experience in areas as outlined below
- Experience in extracting data using SQL from large databases
- Experience in writing complex ETL processes and frameworks for analytics and data management. Must have experience in working on ETL tools.
- Master’s degree or PhD in Statistics, Data Science, Economics, Operations Research, Computer Science, or a similar degree with a focus on statistical methods. A Bachelor’s degree in the same fields with significant, demonstrated professional research experience will also be considered.
- Programming experience in scientific computing language (R, Python, Julia) and the ability to interact with relational data (SQL, Apache Pig, SparkSQL). General purpose programming (Python, Scala, Java) and familiarity with Hadoop is a plus.
- Excellent verbal and written communication skills.
- Experience with TV or digital audience measurement or market research data is a plus.
- Familiarity with systems analysis or systems thinking is a plus.
- Must be comfortable with analyzing complex, high-volume and high-dimension data from varying sources
- Excellent verbal, written and computer communication skills
- Ability to engage with Senior Leaders across all functional departments
- Ability to take on new responsibilities and adapt to changes
About Magic9 Media and Consumer Knowledge Pvt. Ltd.
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We are looking for a Machine Learning Engineer with experience in model deployments. Candidate will be responsible for deploying AI / Machine Learning applications for our manufacturing clients. We expect them to have strong programming skills, and background of deployment of ML models for time series data. They should have a sturdy growth mind set and a strong work ethic. Candidate will interact with the data science team to understand the models and scalability of solution.
Key responsibilities:
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Design and set-up of ML model deployment pipelines and architectures
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Evaluation of the deployed ML models and deployment pipelines
-
Coordination with the data science, data infrastructure team and customer for proper deployment of the models
-
Writing production-ready code following software development principles
-
Testing deployment pipelines
-
Technical documentation of the projects
-
Dashboard preparation for showing the results from the deployed models
Your background:
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Educational Background: B.Tech/M.Tech/BE in STEM fields
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Machine Learning Algorithms
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Supervised, Unsupervised, Timeseries analysis, Time series Feature Engineering
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AI Deployment workflows
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ML Libraries: scikit-learn, pandas, numpy, matplotlib, seaborn, plotly
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Code and Data version control: Git, DVC, etc
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MLOPs: AI Workflow and Pipeline Orchestration Tools
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Docker
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Kubeflow, Airflow, etc
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AWS Sagemaker, GCP, or Azure
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Database management:
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SQL, Timestream DB, InfluxDB
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Visualization Dashboard Platforms
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Grafana, Tableau
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Misc. Tools and Protocols
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Familiarity with Linux based system
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Good to have ML Libraries:
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Pycaret, Pytorch, Tensorflow, TsFresh
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Desirable to have certifications in Data Science tools and methodologies.
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Strong written and verbal communication skills
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Excellent problem solving and data analytical skills
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The ability to drive culture changes in an organization.
Our Team Culture:
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Working for one of the technology leaders in Europe in one of the most innovative and promising industry sectors
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Short decision-making paths and the opportunity to contribute and implement your own ideas
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Positive, motivated, and energetic working atmosphere in a team with experienced Digitization experts and long-term entrepreneurs
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Option to also work from Home
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Steep learning curve and opportunities for personal and professional training and further education
o You’re both relentless and kind, and don’t see these as being mutually
exclusive
o You have a self-directed learning style, an insatiable curiosity, and a
hands-on execution mindset
o You have deep experience working with product and engineering teams
to launch machine learning products that users love in new or rapidly
evolving markets
o You flourish in uncertain environments and can turn incomplete,
conflicting, or ambiguous inputs into solid data-science action plans
o You bring best practices to feature engineering, model development, and
ML operations
o Your experience in deploying and monitoring the performance of models
in production enables us to implement a best-in-class solution
o You have exceptional writing and speaking skills with a talent for
articulating how data science can be applied to solve customer problems
Must-Have Qualifications
o Graduate degree in engineering, data science, mathematics, physics, or
another quantitative field
o 5+ years of hands-on experience in building and deploying production-
grade ML models with ML frameworks (TensorFlow, Keras, PyTorch) and
libraries like scikit-learn
o Track-record in building ML pipelines for time series, classification, and
predictive applications
o Expert level skills in Python for data analysis and visualization, hypothesis
testing, and model building
o Deep experience with ensemble ML approaches including random forests
and xgboost, and experience with databases and querying models for
structured and unstructured data
o A knack for using data visualization and analysis tools to tell a story
o You naturally think quantitatively about problems and work backward
from a customer outcome
What’ll make you stand out (but not required)
o You have a keen awareness or interest in network analysis/graph analysis
or NLP
o You have experience in distributed systems and graph databases
o You have a strong connection to finance teams or closely related
domains, the challenges they face, and a deep appreciation for their
aspirations
Company Name: Intraedge Technologies Ltd (https://intraedge.com/" target="_blank">https://intraedge.com/)
Type: Permanent, Full time
Location: Any
A Bachelor’s degree in computer science, computer engineering, other technical discipline, or equivalent work experience
- 4+ years of software development experience
- 4+ years exp in programming languages- Python, spark, Scala, Hadoop, hive
- Demonstrated experience with Agile or other rapid application development methods
- Demonstrated experience with object-oriented design and coding.
Please mail you rresume to poornimakattherateintraedgedotcomalong with NP, how soon can you join, ECTC, Availability for interview, Location
Responsibilities: - Write and maintain production level code in Python for deploying machine learning models - Create and maintain deployment pipelines through CI/CD tools (preferribly GitLab CI) - Implement alerts and monitoring for prediction accuracy and data drift detection - Implement automated pipelines for training and replacing models - Work closely with with the data science team to deploy new models to production Required Qualifications: - Degree in Computer Science, Data Science, IT or a related discipline. - 2+ years of experience in software engineering or data engineering. - Programming experience in Python - Experience in data profiling, ETL development, testing and implementation - Experience in deploying machine learning models
Good to have: - Experience in AWS resources for ML and data engineering (SageMaker, Glue, Athena, Redshift, S3) - Experience in deploying TensorFlow models - Experience in deploying and managing ML Flow
- Hands-on experience in any Cloud Platform
- Microsoft Azure Experience
Minimum of 4 years’ experience of working on DW/ETL projects and expert hands-on working knowledge of ETL tools.
Experience with Data Management & data warehouse development
Star schemas, Data Vaults, RDBMS, and ODS
Change Data capture
Slowly changing dimensions
Data governance
Data quality
Partitioning and tuning
Data Stewardship
Survivorship
Fuzzy Matching
Concurrency
Vertical and horizontal scaling
ELT, ETL
Spark, Hadoop, MPP, RDBMS
Experience with Dev/OPS architecture, implementation and operation
Hand's on working knowledge of Unix/Linux
Building Complex SQL Queries. Expert SQL and data analysis skills, ability to debug and fix data issue.
Complex ETL program design coding
Experience in Shell Scripting, Batch Scripting.
Good communication (oral & written) and inter-personal skills
Expert SQL and data analysis skill, ability to debug and fix data issue Work closely with business teams to understand their business needs and participate in requirements gathering, while creating artifacts and seek business approval.
Helping business define new requirements, Participating in End user meetings to derive and define the business requirement, propose cost effective solutions for data analytics and familiarize the team with the customer needs, specifications, design targets & techniques to support task performance and delivery.
Propose good design & solutions and adherence to the best Design & Standard practices.
Review & Propose industry best tools & technology for ever changing business rules and data set. Conduct Proof of Concepts (POC) with new tools & technologies to derive convincing benchmarks.
Prepare the plan, design and document the architecture, High-Level Topology Design, Functional Design, and review the same with customer IT managers and provide detailed knowledge to the development team to familiarize them with customer requirements, specifications, design standards and techniques.
Review code developed by other programmers, mentor, guide and monitor their work ensuring adherence to programming and documentation policies.
Work with functional business analysts to ensure that application programs are functioning as defined.
Capture user-feedback/comments on the delivered systems and document it for the client and project manager’s review. Review all deliverables before final delivery to client for quality adherence.
Technologies (Select based on requirement)
Databases - Oracle, Teradata, Postgres, SQL Server, Big Data, Snowflake, or Redshift
Tools – Talend, Informatica, SSIS, Matillion, Glue, or Azure Data Factory
Utilities for bulk loading and extracting
Languages – SQL, PL-SQL, T-SQL, Python, Java, or Scala
J/ODBC, JSON
Data Virtualization Data services development
Service Delivery - REST, Web Services
Data Virtualization Delivery – Denodo
ELT, ETL
Cloud certification Azure
Complex SQL Queries
Data Ingestion, Data Modeling (Domain), Consumption(RDMS)
- 5 years of experience in Business Intelligence development.
- Experience with MicroStrategy toolset: Desktop, Report Services, Architect, OLAP, Administrator
- Strong experience in design, creation, and deployment of reports and dashboards
- Experience with designing reusable MicroStrategy components for business reporting
- Excellent communication skills to interact with users at various levels within the organization.
- Strong SQL skills to perform queries, data/file validation, analysis, profiling, etc, as needed
- Creating and maintaining documentation is a plus
- Ability to work collaboratively in teams and develop meaningful relationships to achieve common goals.
- Experience with ETL and Collibra is a plus
- Previous experience in the banking industry is preferred
Senior Computer Vision Developer
This position is not for freshers. We are looking for candidates with AI/ML/CV experience of at least 4 year in the industry.
Location: Chennai- Guindy Industrial Estate
Duration: Full time role
Company: Mobile Programming (https://www.mobileprogramming.com/" target="_blank">https://www.
Client Name: Samsung
We are looking for a Data Engineer to join our growing team of analytics experts. The hire will be
responsible for expanding and optimizing our data and data pipeline architecture, as well as optimizing
data flow and collection for cross functional teams. The ideal candidate is an experienced data pipeline
builder and data wrangler who enjoy optimizing data systems and building them from the ground up.
The Data Engineer will support our software developers, database architects, data analysts and data
scientists on data initiatives and will ensure optimal data delivery architecture is consistent throughout
ongoing projects. They must be self-directed and comfortable supporting the data needs of multiple
teams, systems and products.
Responsibilities for Data Engineer
Create and maintain optimal data pipeline architecture,
Assemble large, complex data sets that meet functional / non-functional business requirements.
Identify, design, and implement internal process improvements: automating manual processes,
optimizing data delivery, re-designing infrastructure for greater scalability, etc.
Build the infrastructure required for optimal extraction, transformation, and loading of data
from a wide variety of data sources using SQL and AWS big data technologies.
Build analytics tools that utilize the data pipeline to provide actionable insights into customer
acquisition, operational efficiency and other key business performance metrics.
Work with stakeholders including the Executive, Product, Data and Design teams to assist with
data-related technical issues and support their data infrastructure needs.
Create data tools for analytics and data scientist team members that assist them in building and
optimizing our product into an innovative industry leader.
Work with data and analytics experts to strive for greater functionality in our data systems.
Qualifications for Data Engineer
Experience building and optimizing big data ETL pipelines, architectures and data sets.
Advanced working SQL knowledge and experience working with relational databases, query
authoring (SQL) as well as working familiarity with a variety of databases.
Experience performing root cause analysis on internal and external data and processes to
answer specific business questions and identify opportunities for improvement.
Strong analytic skills related to working with unstructured datasets.
Build processes supporting data transformation, data structures, metadata, dependency and
workload management.
A successful history of manipulating, processing and extracting value from large disconnected
datasets.
Working knowledge of message queuing, stream processing and highly scalable ‘big data’ data
stores.
Strong project management and organizational skills.
Experience supporting and working with cross-functional teams in a dynamic environment.
We are looking for a candidate with 3-6 years of experience in a Data Engineer role, who has
attained a Graduate degree in Computer Science, Statistics, Informatics, Information Systems or another quantitative field. They should also have experience using the following software/tools:
Experience with big data tools: Spark, Kafka, HBase, Hive etc.
Experience with relational SQL and NoSQL databases
Experience with AWS cloud services: EC2, EMR, RDS, Redshift
Experience with stream-processing systems: Storm, Spark-Streaming, etc.
Experience with object-oriented/object function scripting languages: Python, Java, Scala, etc.
Skills: Big Data, AWS, Hive, Spark, Python, SQL
Pipelines should be optimised to handle both real time data, batch update data and historical data.
Establish scalable, efficient, automated processes for complex, large scale data analysis.
Write high quality code to gather and manage large data sets (both real time and batch data) from multiple sources, perform ETL and store it in a data warehouse.
Manipulate and analyse complex, high-volume, high-dimensional data from varying sources using a variety of tools and data analysis techniques.
Participate in data pipelines health monitoring and performance optimisations as well as quality documentation.
Interact with end users/clients and translate business language into technical requirements.
Acts independently to expose and resolve problems.
Job Requirements :-
2+ years experience working in software development & data pipeline development for enterprise analytics.
2+ years of working with Python with exposure to various warehousing tools
In-depth working with any of commercial tools like AWS Glue, Ta-lend, Informatica, Data-stage, etc.
Experience with various relational databases like MySQL, MSSql, Oracle etc. is a must.
Experience with analytics and reporting tools (Tableau, Power BI, SSRS, SSAS).
Experience in various DevOps practices helping the client to deploy and scale the systems as per requirement.
Strong verbal and written communication skills with other developers and business client.
Knowledge of Logistics and/or Transportation Domain is a plus.
Hands-on with traditional databases and ERP systems like Sybase and People-soft.
