Data Scientist

5+ years of experience in a Data Engineer role.
 Proficiency in Linux.
 Must have SQL knowledge and experience working with relational databases,
query authoring (SQL) as well as familiarity with databases including Mysql,
Mongo, Cassandra, and Athena.
 Must have experience with Python/Scala.
 Must have experience with Big Data technologies like Apache Spark.
 Must have experience with Apache Airflow.
 Experience with data pipeline and ETL tools like AWS Glue.
 Experience working with AWS cloud services: EC2, S3, RDS, Redshift.

Company Profile:

The company is World's No1 Global management consulting firm.

Job Qualifications
 Graduate or post graduate degree in statistics, economics, econometrics, computer science,
engineering, or mathematics
 2-5 years of relevant experience
 Adept in forecasting, regression analysis and segmentation work
 Understanding of modeling techniques, specifically logistic regression, linear regression, cluster
analysis, CHAID, etc.
 Statistical programming software experience in R & Python, comfortable working with large data
sets; SAS & SQL are also preferred
 Excellent analytical and problem-solving skills, including the ability to disaggregate issues, identify
root causes and recommend solutions
 Excellent time management skills
 Good written and verbal communication skills; understanding of both written and spoken English
 Strong interpersonal skills
 Ability to act autonomously, bringing structure and organization to work
 Creative and action-oriented mindset
 Ability to interact in a fluid, demanding and unstructured environment where priorities evolve
constantly and methodologies are regularly challenged
 Ability to work under pressure and deliver on tight deadlines

Company Profile
XressBees – a logistics company started in 2015 – is amongst the fastest growing companies of its sector. Our
vision to evolve into a strong full-service logistics organization reflects itself in the various lines of business like B2C
logistics 3PL, B2B Xpress, Hyperlocal and Cross border Logistics.
Our strong domain expertise and constant focus on innovation has helped us rapidly evolve as the most trusted
logistics partner of India. XB has progressively carved our way towards best-in-class technology platforms, an
extensive logistics network reach, and a seamless last mile management system.
While on this aggressive growth path, we seek to become the one-stop-shop for end-to-end logistics solutions. Our
big focus areas for the very near future include strengthening our presence as service providers of choice and
leveraging the power of technology to drive supply chain efficiencies.
Job Overview
XpressBees would enrich and scale its end-to-end logistics solutions at a high pace. This is a great opportunity to join
the team working on forming and delivering the operational strategy behind Artificial Intelligence / Machine Learning
and Data Engineering, leading projects and teams of AI Engineers collaborating with Data Scientists. In your role, you
will build high performance AI/ML solutions using groundbreaking AI/ML and BigData technologies. You will need to
understand business requirements and convert them to a solvable data science problem statement. You will be
involved in end to end AI/ML projects, starting from smaller scale POCs all the way to full scale ML pipelines in
production.
Seasoned AI/ML Engineers would own the implementation and productionzation of cutting-edge AI driven algorithmic
components for search, recommendation and insights to improve the efficiencies of the logistics supply chain and
serve the customer better.
You will apply innovative ML tools and concepts to deliver value to our teams and customers and make an impact to
the organization while solving challenging problems in the areas of AI, ML , Data Analytics and Computer Science.
Opportunities for application:
- Route Optimization
- Address / Geo-Coding Engine
- Anomaly detection, Computer Vision (e.g. loading / unloading)
- Fraud Detection (fake delivery attempts)
- Promise Recommendation Engine etc.
- Customer & Tech support solutions, e.g. chat bots.
- Breach detection / prediction
An Artificial Intelligence Engineer would apply himself/herself in the areas of -
- Deep Learning, NLP, Reinforcement Learning
- Machine Learning - Logistic Regression, Decision Trees, Random Forests, XGBoost, etc..
- Driving Optimization via LPs, MILPs, Stochastic Programs, and MDPs
- Operations Research, Supply Chain Optimization, and Data Analytics/Visualization
- Computer Vision and OCR technologies
The AI Engineering team enables internal teams to add AI capabilities to their Apps and Workflows easily via APIs
without needing to build AI expertise in each team – Decision Support, NLP, Computer Vision, for Public Clouds and
Enterprise in NLU, Vision and Conversational AI.Candidate is adept at working with large data sets to find
opportunities for product and process optimization and using models to test the effectiveness of different courses of
action. They must have knowledge using a variety of data mining/data analysis methods, using a variety of data tools,
building, and implementing models, using/creating algorithms, and creating/running simulations. They must be
comfortable working with a wide range of stakeholders and functional teams. The right candidate will have a passion
for discovering solutions hidden in large data sets and working with stakeholders to improve business outcomes.

Roles & Responsibilities
● Develop scalable infrastructure, including microservices and backend, that automates training and
deployment of ML models.
● Building cloud services in Decision Support (Anomaly Detection, Time series forecasting, Fraud detection,
Risk prevention, Predictive analytics), computer vision, natural language processing (NLP) and speech that
work out of the box.
● Brainstorm and Design various POCs using ML/DL/NLP solutions for new or existing enterprise problems.
● Work with fellow data scientists/SW engineers to build out other parts of the infrastructure, effectively
communicating your needs and understanding theirs and address external and internal shareholder's
product challenges.
● Build core of Artificial Intelligence and AI Services such as Decision Support, Vision, Speech, Text, NLP, NLU,
and others.
● Leverage Cloud technology –AWS, GCP, Azure
● Experiment with ML models in Python using machine learning libraries (Pytorch, Tensorflow), Big Data,
Hadoop, HBase, Spark, etc
● Work with stakeholders throughout the organization to identify opportunities for leveraging company data to
drive business solutions.
● Mine and analyze data from company databases to drive optimization and improvement of product
development, marketing techniques and business strategies.
● Assess the effectiveness and accuracy of new data sources and data gathering techniques.
● Develop custom data models and algorithms to apply to data sets.
● Use predictive modeling to increase and optimize customer experiences, supply chain metric and other
business outcomes.
● Develop company A/B testing framework and test model quality.
● Coordinate with different functional teams to implement models and monitor outcomes.
● Develop processes and tools to monitor and analyze model performance and data accuracy.
● Develop scalable infrastructure, including microservices and backend, that automates training and
deployment of ML models.
● Brainstorm and Design various POCs using ML/DL/NLP solutions for new or existing enterprise problems.
● Work with fellow data scientists/SW engineers to build out other parts of the infrastructure, effectively
communicating your needs and understanding theirs and address external and internal shareholder's
product challenges.
● Deliver machine learning and data science projects with data science techniques and associated libraries
such as AI/ ML or equivalent NLP (Natural Language Processing) packages. Such techniques include a good
to phenomenal understanding of statistical models, probabilistic algorithms, classification, clustering, deep
learning or related approaches as it applies to financial applications.
● The role will encourage you to learn a wide array of capabilities, toolsets and architectural patterns for
successful delivery.
What is required of you?
You will get an opportunity to build and operate a suite of massive scale, integrated data/ML platforms in a broadly
distributed, multi-tenant cloud environment.
● B.S., M.S., or Ph.D. in Computer Science, Computer Engineering
● Coding knowledge and experience with several languages: C, C++, Java,JavaScript, etc.
● Experience with building high-performance, resilient, scalable, and well-engineered systems
● Experience in CI/CD and development best practices, instrumentation, logging systems
● Experience using statistical computer languages (R, Python, SLQ, etc.) to manipulate data and draw insights
from large data sets.
● Experience working with and creating data architectures.
● Good understanding of various machine learning and natural language processing technologies, such as
classification, information retrieval, clustering, knowledge graph, semi-supervised learning and ranking.

● Knowledge and experience in statistical and data mining techniques: GLM/Regression, Random Forest,
Boosting, Trees, text mining, social network analysis, etc.
● Knowledge on using web services: Redshift, S3, Spark, Digital Ocean, etc.
● Knowledge on creating and using advanced machine learning algorithms and statistics: regression,
simulation, scenario analysis, modeling, clustering, decision trees, neural networks, etc.
● Knowledge on analyzing data from 3rd party providers: Google Analytics, Site Catalyst, Core metrics,
AdWords, Crimson Hexagon, Facebook Insights, etc.
● Knowledge on distributed data/computing tools: Map/Reduce, Hadoop, Hive, Spark, MySQL, Kafka etc.
● Knowledge on visualizing/presenting data for stakeholders using: Quicksight, Periscope, Business Objects,
D3, ggplot, Tableau etc.
● Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural
networks, etc.) and their real-world advantages/drawbacks.
● Knowledge of advanced statistical techniques and concepts (regression, properties of distributions,
statistical tests, and proper usage, etc.) and experience with applications.
● Experience building data pipelines that prep data for Machine learning and complete feedback loops.
● Knowledge of Machine Learning lifecycle and experience working with data scientists
● Experience with Relational databases and NoSQL databases
● Experience with workflow scheduling / orchestration such as Airflow or Oozie
● Working knowledge of current techniques and approaches in machine learning and statistical or
mathematical models
● Strong Data Engineering & ETL skills to build scalable data pipelines. Exposure to data streaming stack (e.g.
Kafka)
● Relevant experience in fine tuning and optimizing ML (especially Deep Learning) models to bring down
serving latency.
● Exposure to ML model productionzation stack (e.g. MLFlow, Docker)
● Excellent exploratory data analysis skills to slice & dice data at scale using SQL in Redshift/BigQuery.

Carsome’s Data Department is on the lookout for a Data Scientist/Data Science Lead who has a strong passion in building data powered products.

 

Data Science function under the Data Department has a responsibility for standardisation of methods, mentoring team of data science resources/interns, including code libraries and documentation, quality assurance of outputs, modeling techniques and statistics, leveraging a variety of technologies, open-source languages, and cloud computing platform. 

 

You will get to lead & implement projects such as price optimization/prediction, enabling iconic personalization experiences for our customer, inventory optimization etc.

 

Job Descriptions

 

• Identifying and integrating datasets that can be leveraged through our product and work closely with data engineering team to develop data products.
• Execute analytical experiments methodically to help solve various problems and make a true impact across functions such as operations, finance, logistics, marketing. 
• Identify, prioritize, and design testing opportunities that will inform algorithm enhancements. 
• Devise and utilize algorithms and models to mine big data stores, perform data and error analysis to improve models and clean and validate data for uniformity and accuracy.
• Unlock insights by analyzing large amounts of complex website traffic and transactional data. 
• Implement analytical models into production by collaborating with data analytics engineers.

 

Technical Requirements

 

• Expertise in model design, training, evaluation, and implementation ML Algorithm expertise K-nearest neighbors, Random Forests, Naive Bayes, Regression Models. PyTorch, TensorFlow, Keras, deep learning expertise, tSNE, gradient boosting expertise, regression implementation expertise, Python, Pyspark, SQL, R, AWS Sagemaker /personalize etc.
• Machine Learning / Data Science Certification

 

Experience & Education 

 

• Bachelor’s in Engineering / Master’s in Data Science  / Postgraduate Certificate in Data Science. 

We are looking for a python developer who has a passion to drive more solar and clean energy in the world working with us. The software helps anyone understand how much solar could be put up on a rooftop and calculates how many units of clean energy the solar PV system would generate, along with how much savings the homeowner would have. This is a crucial step in helping educate people who want to go solar, but aren’t completely convinced of solar's value proposition. If you are interested in bringing the latest technologies to the fast-growing solar industry and want to help society transition to a more sustainable future, we would love to hear from you!

 

You will -

- Be an early employee at a growing startup and help shape the team culture

- Safeguard code quality on their team, reviewing others’ code with an eye to performance and maintainability

- Be trusted to take point on complex product initiatives

- Work in a ownership driven, micro-management free environment

 

You should have:

- Strong programming fundamentals. (if you don’t officially have a CS degree but know programming, it’s fine with us!)

- Have a strong problem solving attitude.

- Experience with solar or electrical modelling is a plus, although not required.

Job Title: Data Architect
Job Location: Chennai

Job Summary
The Engineering team is seeking a Data Architect. As a Data Architect, you will drive a
Data Architecture strategy across various Data Lake platforms. You will help develop
reference architecture and roadmaps to build highly available, scalable and distributed
data platforms using cloud based solutions to process high volume, high velocity and
wide variety of structured and unstructured data. This role is also responsible for driving
innovation, prototyping, and recommending solutions. Above all, you will influence how
users interact with Conde Nast’s industry-leading journalism.
Primary Responsibilities
Data Architect is responsible for
• Demonstrated technology and personal leadership experience in architecting,
designing, and building highly scalable solutions and products.
• Enterprise scale expertise in data management best practices such as data integration,
data security, data warehousing, metadata management and data quality.
• Extensive knowledge and experience in architecting modern data integration
frameworks, highly scalable distributed systems using open source and emerging data
architecture designs/patterns.
• Experience building external cloud (e.g. GCP, AWS) data applications and capabilities is
highly desirable.
• Expert ability to evaluate, prototype and recommend data solutions and vendor
technologies and platforms.
• Proven experience in relational, NoSQL, ELT/ETL technologies and in-memory
databases.
• Experience with DevOps, Continuous Integration and Continuous Delivery technologies
is desirable.
• This role requires 15+ years of data solution architecture, design and development
delivery experience.
• Solid experience in Agile methodologies (Kanban and SCRUM)
Required Skills
• Very Strong Experience in building Large Scale High Performance Data Platforms.
• Passionate about technology and delivering solutions for difficult and intricate
problems. Current on Relational Databases and No sql databases on cloud.
• Proven leadership skills, demonstrated ability to mentor, influence and partner with
cross teams to deliver scalable robust solutions..
• Mastery of relational database, NoSQL, ETL (such as Informatica, Datastage etc) /ELT
and data integration technologies.
• Experience in any one of Object Oriented Programming (Java, Scala, Python) and
Spark.
• Creative view of markets and technologies combined with a passion to create the
future.
• Knowledge on cloud based Distributed/Hybrid data-warehousing solutions and Data
Lake knowledge is mandate.
• Good understanding of emerging technologies and its applications.
• Understanding of code versioning tools such as GitHub, SVN, CVS etc.
• Understanding of Hadoop Architecture and Hive SQL
• Knowledge in any one of the workflow orchestration
• Understanding of Agile framework and delivery
•
Preferred Skills:
● Experience in AWS and EMR would be a plus
● Exposure in Workflow Orchestration like Airflow is a plus
● Exposure in any one of the NoSQL database would be a plus
● Experience in Databricks along with PySpark/Spark SQL would be a plus
● Experience with the Digital Media and Publishing domain would be a
plus
● Understanding of Digital web events, ad streams, context models

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.

1. Develop novel computer vision/NLP algorithms
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

Key Responsibilities:

• Partnering with clients and internal business owners (product, marketing, edit, etc.) to understand needs and develop models and products for Kaleidofin business line.
• Good understanding of the underlying business and workings of cross functional teams for successful execution
• Design and develop analyses based on business requirement needs and challenges.
• Leveraging statistical analysis on consumer research and data mining projects, including segmentation, clustering, factor analysis, multivariate regression, predictive modeling, hyperparameter tuning, ensembling etc.
• Providing statistical analysis on custom research projects and consult on A/B testing and other statistical analysis as needed. Other reports and custom analysis as required.
• Identify and use appropriate investigative and analytical technologies to interpret and verify results.
• Apply and learn a wide variety of tools and languages to achieve results
• Use best practices to develop statistical and/ or machine learning techniques to build models that address business needs.
• Collaborate with the team to improve the effectiveness of business decisions using data and machine learning/predictive modeling.
• Innovate on projects by using new modeling techniques or tools.
• Utilize effective project planning techniques to break down complex projects into tasks and ensure deadlines are kept.
• Communicate findings to team and leadership to ensure models are well understood and incorporated into business processes.

 

Skills:

• 2+ year experience in advanced analytics, model building, statistical modeling, optimization, and machine learning algorithms.
• Machine Learning Algorithms: Crystal clear understanding, coding, implementation, error analysis, model tuning knowledge on Linear Regression, Logistic Regression, SVM, shallow Neural Networks, clustering, Decision Trees, Random forest, Boosting trees, Recommender Systems, ARIMA and Anomaly Detection. Feature selection, hyper parameters tuning, model selection and error analysis, ensemble methods.
• Strong with programming languages like Python and data processing using SQL or equivalent and ability to experiment with newer open source tools
• Experience in normalizing data to ensure it is homogeneous and consistently formatted to enable sorting, query and analysis.
• Experience designing, developing, implementing and maintaining a database and programs to manage data analysis efforts.
• Experience with big data and cloud computing viz. Spark, Hadoop (MapReduce, PIG, HIVE)
• Experience in risk and credit scoring domains preferred

We are an early stage startup working in the space of analytics, big data, machine learning, data visualization on multiple platforms and SaaS. We have our offices in Palo Alto and WTC, Kharadi, Pune and got some marque names as our customers. We are looking for really good Python programmer who MUST have scientific programming experience (Python, etc.) Hands-on with numpy and the Python scientific stack is a must. Demonstrated ability to track and work with 100s-1000s of files and GB-TB of data. Exposure to ML and Data mining algorithms. Need to be comfortable working in a Unix environment and SQL. You will be required to do following: Using command line tools to perform data conversion and analysis Supporting other team members in retrieving and archiving experimental results Quickly writing scripts to automate routine analysis tasks Creating insightful, simple graphics to represent complex trends Explore/design/invent new tools and design patterns to solve complex big data problems Experience working on a long-term, lab-based project (academic experience acceptable)