culture and operating norms as a result of the fast-paced nature of a new, high-growth
organization.
• 7+ years of Industry experience primarily related to Unstructured Text Data and NLP
(PhD work and internships will be considered if they are related to unstructured text
in lieu of industry experience but not more than 2 years will be accounted towards
industry experience)
• Develop Natural Language Medical/Healthcare documents comprehension related
products to support Health business objectives, products and improve
processing efficiency, reducing overall healthcare costs
• Gather external data sets; build synthetic data and label data sets as per the needs
for NLP/NLR/NLU
• Apply expert software engineering skills to build Natural Language products to
improve automation and improve user experiences leveraging unstructured data storage, Entity Recognition, POS Tagging, ontologies, taxonomies, data mining,
information retrieval techniques, machine learning approach, distributed and cloud
computing platforms
• Own the Natural Language and Text Mining products — from platforms to systems
for model training, versioning, deploying, storage and testing models with creating
real time feedback loops to fully automated services
• Work closely and collaborate with Data Scientists, Machine Learning engineers, IT
teams and Business stakeholders spread out across various locations in US and India
to achieve business goals
• Provide mentoring to other Data Scientist and Machine Learning Engineers
• Strong understanding of mathematical concepts including but not limited to linear
algebra, Advanced calculus, partial differential equations and statistics including
Bayesian approaches
• Strong programming experience including understanding of concepts in data
structures, algorithms, compression techniques, high performance computing,
distributed computing, and various computer architecture
• Good understanding and experience with traditional data science approaches like
sampling techniques, feature engineering, classification and regressions, SVM, trees,
model evaluations
• Additional course work, projects, research participation and/or publications in
Natural Language processing, reasoning and understanding, information retrieval,
text mining, search, computational linguistics, ontologies, semantics
• Experience with developing and deploying products in production with experience
in two or more of the following languages (Python, C++, Java, Scala)
• Strong Unix/Linux background and experience with at least one of the following
cloud vendors like AWS, Azure, and Google for 2+ years
• Hands on experience with one or more of high-performance computing and
distributed computing like Spark, Dask, Hadoop, CUDA distributed GPU (2+ years)
• Thorough understanding of deep learning architectures and hands on experience
with one or more frameworks like tensorflow, pytorch, keras (2+ years)
• Hands on experience with libraries and tools like Spacy, NLTK, Stanford core NLP,
Genism, johnsnowlabs for 5+ years
• Understanding business use cases and be able to translate them to team with a
vision on how to implement
• Identify enhancements and build best practices that can help to improve the
productivity of the team.
About MNC
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Experience with various stream processing and batch processing tools (Kafka,
Spark etc). Programming with Python.
● Experience with relational and non-relational databases.
● Fairly good understanding of AWS (or any equivalent).
Key Responsibilities
● Design new systems and redesign existing systems to work at scale.
● Care about things like fault tolerance, durability, backups and recovery,
performance, maintainability, code simplicity etc.
● Lead a team of software engineers and help create an environment of ownership
and learning.
● Introduce best practices of software development and ensure their adoption
across the team.
● Help set and maintain coding standards for the team.
Analytics Job Description
We are hiring an Analytics Engineer to help drive our Business Intelligence efforts. You will
partner closely with leaders across the organization, working together to understand the how
and why of people, team and company challenges, workflows and culture. The team is
responsible for delivering data and insights that drive decision-making, execution, and
investments for our product initiatives.
You will work cross-functionally with product, marketing, sales, engineering, finance, and our
customer-facing teams enabling them with data and narratives about the customer journey.
You’ll also work closely with other data teams, such as data engineering and product analytics,
to ensure we are creating a strong data culture at Blend that enables our cross-functional partners
to be more data-informed.
Role : DataEngineer
Please find below the JD for the DataEngineer Role..
Location: Guindy,Chennai
How you’ll contribute:
• Develop objectives and metrics, ensure priorities are data-driven, and balance short-
term and long-term goals
• Develop deep analytical insights to inform and influence product roadmaps and
business decisions and help improve the consumer experience
• Work closely with GTM and supporting operations teams to author and develop core
data sets that empower analyses
• Deeply understand the business and proactively spot risks and opportunities
• Develop dashboards and define metrics that drive key business decisions
• Build and maintain scalable ETL pipelines via solutions such as Fivetran, Hightouch,
and Workato
• Design our Analytics and Business Intelligence architecture, assessing and
implementing new technologies that fitting
• Work with our engineering teams to continually make our data pipelines and tooling
more resilient
Who you are:
• Bachelor’s degree or equivalent required from an accredited institution with a
quantitative focus such as Economics, Operations Research, Statistics, Computer Science OR 1-3 Years of Experience as a Data Analyst, Data Engineer, Data Scientist
• Must have strong SQL and data modeling skills, with experience applying skills to
thoughtfully create data models in a warehouse environment.
• A proven track record of using analysis to drive key decisions and influence change
• Strong storyteller and ability to communicate effectively with managers and
executives
• Demonstrated ability to define metrics for product areas, understand the right
questions to ask and push back on stakeholders in the face of ambiguous, complex
problems, and work with diverse teams with different goals
• A passion for documentation.
• A solution-oriented growth mindset. You’ll need to be a self-starter and thrive in a
dynamic environment.
• A bias towards communication and collaboration with business and technical
stakeholders.
• Quantitative rigor and systems thinking.
• Prior startup experience is preferred, but not required.
• Interest or experience in machine learning techniques (such as clustering, decision
tree, and segmentation)
• Familiarity with a scientific computing language, such as Python, for data wrangling
and statistical analysis
• Experience with a SQL focused data transformation framework such as dbt
• Experience with a Business Intelligence Tool such as Mode/Tableau
Mandatory Skillset:
-Very Strong in SQL
-Spark OR pyspark OR Python
-Shell Scripting
At Livello we building machine-learning-based demand forecasting tools as well as computer-vision-based multi-camera product recognition solutions that detects people and products to track the inserted/removed items on shelves based on the hand movement of users. We are building models to determine real-time inventory levels, user behaviour as well as predicting how much of each product needs to be reordered so that the right products are delivered to the right locations at the right time, to fulfil customer demand.
Responsibilities
- Lead the CV and DS Team
- Work in the area of Computer Vision and Machine Learning, with focus on product (primarily food) and people recognition (position, movement, age, gender, DSGVO compliant).
- Your work will include formulation and development of a Machine Learning models to solve the underlying problem.
- You help build our smart supply chain system, keep up to date with the latest algorithmic improvements in forecasting and predictive areas, challenge the status quo
- Statistical data modelling and machine learning research.
- Conceptualize, implement and evaluate algorithmic solutions for supply forecasting, inventory optimization, predicting sales, and automating business processes
- Conduct applied research to model complex dependencies, statistical inference and predictive modelling
- Technological conception, design and implementation of new features
- Quality assurance of the software through planning, creation and execution of tests
- Work with a cross-functional team to define, build, test, and deploy applications
Requirements:
- Master/PHD in Mathematics, Statistics, Engineering, Econometrics, Computer Science or any related fields.
- 3-4 years of experience with computer vision and data science.
- Relevant Data Science experience, deep technical background in applied data science (machine learning algorithms, statistical analysis, predictive modelling, forecasting, Bayesian methods, optimization techniques).
- Experience building production-quality and well-engineered Computer Vision and Data Science products.
- Experience in image processing, algorithms and neural networks.
- Knowledge of the tools, libraries and cloud services for Data Science. Ideally Google Cloud Platform
- Solid Python engineering skills and experience with Python, Tensorflow, Docker
- Cooperative and independent work, analytical mindset, and willingness to take responsibility
- Fluency in English, both written and spoken.
- Design the architecture of our big data platform
- Perform and oversee tasks such as writing scripts, calling APIs, web scraping, and writing SQL queries
- Design and implement data stores that support the scalable processing and storage of our high-frequency data
- Maintain our data pipeline
- Customize and oversee integration tools, warehouses, databases, and analytical systems
- Configure and provide availability for data-access tools used by all data scientists
We at Thena are looking for a Machine Learning Engineer with 2-4 years of industry experience to join our team. The ideal candidate will be passionate about developing and deploying ML models that drive business value and have a strong background in ML Ops.
Responsibilities:
- Develop, fine-tune, and deploy ML models for B2B customer communication and collaboration use cases.
- Collaborate with cross-functional teams to define requirements, design models, and deploy them in production.
- Optimize model performance and accuracy through experimentation, iteration, and testing.
- Build and maintain ML infrastructure and tools to support model development and deployment.
- Stay up-to-date with the latest research and best practices in ML, and share knowledge with the team.
Qualifications:
- 2-4 years of industry experience in machine learning engineering, with a focus on natural language processing (NLP) and text classification models.
- Experience with ML Ops, including deploying and managing ML models in production environments.
- Proficiency in Python and deep learning frameworks such as PyTorch or TensorFlow.
- Experience with Embeddings and building on top of LLMs.
- Strong problem-solving and analytical skills, with the ability to develop creative solutions to complex problems.
- Strong communication skills, with the ability to collaborate effectively with cross-functional teams.
- Bachelor's or Master's degree in Computer Science, Electrical Engineering, or a related field.
Job Description - Sr Azure Data Engineer
Roles & Responsibilities:
- Hands-on programming in C# / .Net,
- Develop serverless applications using Azure Function Apps.
- Writing complex SQL Queries, Stored procedures, and Views.
- Creating Data processing pipeline(s).
- Develop / Manage large-scale Data Warehousing and Data processing solutions.
- Provide clean, usable data and recommend data efficiency, quality, and data integrity.
Skills
- Should have working experience on C# /.Net.
- Proficient with writing SQL queries, Stored Procedures, and Views
- Should have worked on Azure Cloud Stack.
- Should have working experience ofin developing serverless code.
- Must have MANDATORILY worked on Azure Data Factory.
Experience
- 4+ years of relevant experience
2. Build large datasets that will be used to train the models
3. Empirically evaluate related research works
4. Train and evaluate deep learning architectures on multiple large scale datasets
5. Collaborate with the rest of the research team to produce high-quality research
- We are looking for an experienced data engineer to join our team.
- The preprocessing involves ETL tasks, using pyspark, AWS Glue, staging data in parquet formats on S3, and Athena
To succeed in this data engineering position, you should care about well-documented, testable code and data integrity. We have devops who can help with AWS permissions.
We would like to build up a consistent data lake with staged, ready-to-use data, and to build up various scripts that will serve as blueprints for various additional data ingestion and transforms.
If you enjoy setting up something which many others will rely on, and have the relevant ETL expertise, we’d like to work with you.
Responsibilities
- Analyze and organize raw data
- Build data pipelines
- Prepare data for predictive modeling
- Explore ways to enhance data quality and reliability
- Potentially, collaborate with data scientists to support various experiments
Requirements
- Previous experience as a data engineer with the above technologies
- Must have 5-8 years of experience in handling data
- Must have the ability to interpret large amounts of data and to multi-task
- Must have strong knowledge of and experience with programming (Python), Linux/Bash scripting, databases(SQL, etc)
- Must have strong analytical and critical thinking to resolve business problems using data and tech
- Must have domain familiarity and interest of – Cloud technologies (GCP/Azure Microsoft/ AWS Amazon), open-source technologies, Enterprise technologies
- Must have the ability to collect, organize, analyze, and disseminate significant amounts of information with attention to detail and accuracy.
- Must have good communication skills
- Working knowledge/exposure to ElasticSearch, PostgreSQL, Athena, PrestoDB, Jupyter Notebook