- Passionate about search & AI technologies. Open to collaborating with colleagues & external contributors.
- Good understanding of the mainstream deep learning models from multiple domains: computer vision, NLP, reinforcement learning, model optimization, etc.
- Hands-on experience on deep learning frameworks, e.g. Tensorflow, Pytorch, MXNet, BERT. Able to implement the latest DL model using existing API, open-source libraries in a short time.
- Hands-on experience with the Cloud-Native techniques. Good understanding of web services and modern software technologies.
- Maintained/contributed machine learning projects, familiar with the agile software development process, CICD workflow, ticket management, code-review, version control, etc.
- Skilled in the following programming languages: Python 3.
- Good English skills especially for writing and reading documentation

About Hammoq
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Responsibilities include:
- Convert the machine learning models into application program interfaces (APIs) so that other applications can use it
- Build AI models from scratch and help the different components of the organization (such as product managers and stakeholders) understand what results they gain from the model
- Build data ingestion and data transformation infrastructure
- Automate infrastructure that the data science team uses
- Perform statistical analysis and tune the results so that the organization can make better-informed decisions
- Set up and manage AI development and product infrastructure
- Be a good team player, as coordinating with others is a must
1+ years of proven experience in ML/AI with Python
Work with the manager through the entire analytical and machine learning model life cycle:
⮚ Define the problem statement
⮚ Build and clean datasets
⮚ Exploratory data analysis
⮚ Feature engineering
⮚ Apply ML algorithms and assess the performance
⮚ Codify for deployment
⮚ Test and troubleshoot the code
⮚ Communicate analysis to stakeholders
Technical Skills
⮚ Proven experience in usage of Python and SQL
⮚ Excellent in programming and statistics
⮚ Working knowledge of tools and utilities - AWS, DevOps with Git, Selenium, Postman, Airflow, PySpark
1.Advanced knowledge of statistical techniques, NLP, machine learning algorithms and deep
learning
frameworks like Tensorflow, Theano, Keras, Pytorch
2. Proficiency with modern statistical modeling (regression, boosting trees, random forests,
etc.),
machine learning (text mining, neural network, NLP, etc.), optimization (linear
optimization,
nonlinear optimization, stochastic optimization, etc.) methodologies.
3. Build complex predictive models using ML and DL techniques with production quality
code and jointly
own complex data science workflows with the Data Engineering team.
4. Familiar with modern data analytics architecture and data engineering technologies
(SQL and No-SQL databases)
5. Knowledge of REST APIs and Web Services
6. Experience with Python, R, sh/bash
Required Skills (Non-Technical):-
1. Fluent in English Communication (Spoken and verbal)
2. Should be a team player
3. Should have a learning aptitude
4. Detail-oriented, analytical and inquisitive
5. Ability to work independently and with others
6. Extremely organized with strong time-management skills
7. Problem Solving & Critical Thinking
Required Experience Level :- Senior level- 4+Years
Work Location : Pune preferred, Remote option available
Work Timing : 2:30 PM to 11:30 PM IST
Job Description:
The data science team is responsible for solving business problems with complex data. Data complexity could be characterized in terms of volume, dimensionality and multiple touchpoints/sources. We understand the data, ask fundamental-first-principle questions, apply our analytical and machine learning skills to solve the problem in the best way possible.
Our ideal candidate
The role would be a client facing one, hence good communication skills are a must.
The candidate should have the ability to communicate complex models and analysis in a clear and precise manner.
The candidate would be responsible for:
- Comprehending business problems properly - what to predict, how to build DV, what value addition he/she is bringing to the client, etc.
- Understanding and analyzing large, complex, multi-dimensional datasets and build features relevant for business
- Understanding the math behind algorithms and choosing one over another
- Understanding approaches like stacking, ensemble and applying them correctly to increase accuracy
Desired technical requirements
- Proficiency with Python and the ability to write production-ready codes.
- Experience in pyspark, machine learning and deep learning
- Big data experience, e.g. familiarity with Spark, Hadoop, is highly preferred
- Familiarity with SQL or other databases.
About Kloud9:
Kloud9 exists with the sole purpose of providing cloud expertise to the retail industry. Our team of cloud architects, engineers and developers help retailers launch a successful cloud initiative so you can quickly realise the benefits of cloud technology. Our standardised, proven cloud adoption methodologies reduce the cloud adoption time and effort so you can directly benefit from lower migration costs.
Kloud9 was founded with the vision of bridging the gap between E-commerce and cloud. The E-commerce of any industry is limiting and poses a huge challenge in terms of the finances spent on physical data structures.
At Kloud9, we know migrating to the cloud is the single most significant technology shift your company faces today. We are your trusted advisors in transformation and are determined to build a deep partnership along the way. Our cloud and retail experts will ease your transition to the cloud.
Our sole focus is to provide cloud expertise to retail industry giving our clients the empowerment that will take their business to the next level. Our team of proficient architects, engineers and developers have been designing, building and implementing solutions for retailers for an average of more than 20 years.
We are a cloud vendor that is both platform and technology independent. Our vendor independence not just provides us with a unique perspective into the cloud market but also ensures that we deliver the cloud solutions available that best meet our clients' requirements.
Responsibilities:
● Studying, transforming, and converting data science prototypes
● Deploying models to production
● Training and retraining models as needed
● Analyzing the ML algorithms that could be used to solve a given problem and ranking them by their respective scores
● Analyzing the errors of the model and designing strategies to overcome them
● Identifying differences in data distribution that could affect model performance in real-world situations
● Performing statistical analysis and using results to improve models
● Supervising the data acquisition process if more data is needed
● Defining data augmentation pipelines
● Defining the pre-processing or feature engineering to be done on a given dataset
● To extend and enrich existing ML frameworks and libraries
● Understanding when the findings can be applied to business decisions
● Documenting machine learning processes
Basic requirements:
● 4+ years of IT experience in which at least 2+ years of relevant experience primarily in converting data science prototypes and deploying models to production
● Proficiency with Python and machine learning libraries such as scikit-learn, matplotlib, seaborn and pandas
● Knowledge of Big Data frameworks like Hadoop, Spark, Pig, Hive, Flume, etc
● Experience in working with ML frameworks like TensorFlow, Keras, OpenCV
● Strong written and verbal communications
● Excellent interpersonal and collaboration skills.
● Expertise in visualizing and manipulating big datasets
● Familiarity with Linux
● Ability to select hardware to run an ML model with the required latency
● Robust data modelling and data architecture skills.
● Advanced degree in Computer Science/Math/Statistics or a related discipline.
● Advanced Math and Statistics skills (linear algebra, calculus, Bayesian statistics, mean, median, variance, etc.)
Nice to have
● Familiarity with Java, and R code writing.
● 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
● Finding available datasets online that could be used for training
Why Explore a Career at Kloud9:
With job opportunities in prime locations of US, London, Poland and Bengaluru, we help build your career paths in cutting edge technologies of AI, Machine Learning and Data Science. Be part of an inclusive and diverse workforce that's changing the face of retail technology with their creativity and innovative solutions. Our vested interest in our employees translates to deliver the best products and solutions to our customers.
**Education:
Qualification – Any engineering graduate with STRONG programming and logical reasoning skills.
**Minimum years of Experience:2 – 5 years**
Required Skills:
Previous experience as a Data Engineer or in a similar role.
Technical expertise with data models, data mining, and segmentation techniques.
**Knowledge of programming languages (e. g. Java and Python).
Hands-on experience with SQL Programming
Hands-on experience with Python Programming
Knowledge of these tools DBT, ADF, Snowflakes, and Databricks would be added advantage for our current project.**
Strong numerical and analytical skills.
Experience in dealing directly with customers and internal sales organizations.
Strong written and verbal communication, including technical writing skills.
Good to have: Hands-on experience in Cloud services.
Knowledge with ML
Data Warehouse builds (DB, SQL, ETL, Reporting Tools like Power BI…)
Do share your profile to gayathrirajagopalan @jmangroup.com
Job Location: India
Job Summary
We at CondeNast are looking for a data science manager for the content intelligence
workstream primarily, although there might be some overlap with other workstreams. The
position is based out of Chennai and shall report to the head of the data science team, Chennai
Responsibilities:
1. Ideate new opportunities within the content intelligence workstream where data Science can
be applied to increase user engagement
2. Partner with business and translate business and analytics strategies into multiple short-term
and long-term projects
3. Lead data science teams to build quick prototypes to check feasibility and value to business
and present to business
4. Formulate the business problem into an machine learning/AI problem
5. Review & validate models & help improve the accuracy of model
6. Socialize & present the model insights in a manner that business can understand
7. Lead & own the entire value chain of a project/initiative life cycle - Interface with business,
understand the requirements/specifications, gather data, prepare it, train,validate, test the
model, create business presentations to communicate insights, monitor/track the performance
of the solution and suggest improvements
8. Work closely with ML engineering teams to deploy models to production
9. Work closely with data engineering/services/BI teams to help develop data stores, intuitive
visualizations for the products
10. Setup career paths & learning goals for reportees & mentor them
Required Skills:
1. 5+ years of experience in leading Data Science & Advanced analytics projects with a focus on
building recommender systems and 10-12 years of overall experience
2. Experience in leading data science teams to implement recommender systems using content
based, collaborative filtering, embedding techniques
3. Experience in building propensity models, churn prediction, NLP - language models,
embeddings, recommendation engine etc
4. Master’s degree with an emphasis in a quantitative discipline such as statistics, engineering,
economics or mathematics/ Degree programs in data science/ machine learning/ artificial
intelligence
5. Exceptional Communication Skills - verbal and written
6. Moderate level proficiency in SQL, Python
7. Needs to have demonstrated continuous learning through external certifications, degree
programs in machine learning & artificial intelligence
8. Knowledge of Machine learning algorithms & understanding of how they work
9. Knowledge of Reinforcement Learning
Preferred Qualifications
1. Expertise in libraries for data science - pyspark(Databricks), scikit-learn, pandas, numpy,
matplotlib, pytorch/tensorflow/keras etc
2. Working Knowledge of deep learning models
3. Experience in ETL/ data engineering
4. Prior experience in e-commerce, media & publishing domain is a plus
5. Experience in digital advertising is a plus
About Condé Nast
CONDÉ NAST INDIA (DATA)
Over the years, Condé Nast successfully expanded and diversified into digital, TV, and social
platforms - in other words, a staggering amount of user data. Condé Nast made the right move
to invest heavily in understanding this data and formed a whole new Data team entirely
dedicated to data processing, engineering, analytics, and visualization. This team helps drive
engagement, fuel process innovation, further content enrichment, and increase market
revenue. The Data team aimed to create a company culture where data was the common
language and facilitate an environment where insights shared in real-time could improve
performance.
The Global Data team operates out of Los Angeles, New York, Chennai, and London. The team
at Condé Nast Chennai works extensively with data to amplify its brands' digital capabilities and
boost online revenue. We are broadly divided into four groups, Data Intelligence, Data
Engineering, Data Science, and Operations (including Product and Marketing Ops, Client
Services) along with Data Strategy and monetization. The teams built capabilities and products
to create data-driven solutions for better audience engagement.
What we look forward to:
We want to welcome bright, new minds into our midst and work together to create diverse
forms of self-expression. At Condé Nast, we encourage the imaginative and celebrate the
extraordinary. We are a media company for the future, with a remarkable past. We are Condé
Nast, and It Starts Here.
The role involves computer vision tasks including development, customization and training of Convolutional Neural Networks (CNNs); application of ML techniques (SVM, regression, clustering etc. ) and traditional Image Processing (OpenCV etc. ). The role is research focused and would involve going through and implementing existing research papers, deep dive of problem analysis, generating new ideas, automating and optimizing key processes.
Requirements:
- 2 - 4 years of relevant experience in solving complex real-world problems at scale via deep learning, computer vision or AI
- Python, cuDNN, Tensorflow/PyTorch/Keras (or similar Deep Learning frameworks).
- CNNs, RNNs, Transfer learning (for image classification, segmentation, object detection etc).
- Image Processing techniques using OpenCV or other white-box image feature extraction algorithms.
- End to end deployment of deep learning models.
- Key Responsibilities : Use cases to support use case analysis E2E, define capabilities, understand the data and model Machine Learning Operations MLOps Azure Machine Learning, Azure Cognitive Services, Azure DevOps, Overall Azure Cloud Experience, Powershell, DSVM, AML Compute / Training Clusters Azure Infrastructure Experience, Python, Big Data Python Scripting 8 Automate ML models deployments, Manage, monitor, troubleshoot machine learning infrastructure and Setup ML Pipe lines
- Technical Experience : Proven skills experience in Azure AI ML solution design and architecture based solution using Azure Cloud capabilities AML / AKS Proven record of embedding advanced analytical models into business processes Collaborate in multi-functional teams to evaluate business activities, and then develop innovative and effective approaches to tackle teams analytics problems and communicate results bitbucket, Nodejs, PowerBI SQL, Python
- Experience in setting up MLOps framework for AI ML team

