11+ DS Jobs in Delhi, NCR and Gurgaon | DS Job openings in Delhi, NCR and Gurgaon

 

What you need to have:

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.

 

What you need to have:

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.

Responsibilities: 

• Identify complex business problems and work towards building analytical solutions in-order to create large business impact.
• Demonstrate leadership through innovation in software and data products from ideation/conception through design, development and ongoing enhancement, leveraging user research techniques, traditional data tools, and techniques from the data science toolkit such as predictive modelling, NLP, statistical analysis, vector space modelling, machine learning etc.
• Collaborate and ideate with cross-functional teams to identify strategic questions for the business that can be solved and champion the effectiveness of utilizing data, analytics, and insights to shape business.
• Contribute to company growth efforts, increasing revenue and supporting other key business outcomes using analytics techniques.
• Focus on driving operational efficiencies by use of data and analytics to impact cost and employee efficiency.
• Baseline current analytics capability, ensure optimum utilization and continued advancement to stay abridge with industry developments.
• Establish self as a strategic partner with stakeholders, focused on full innovation system and fully supportive of initiatives from early stages to activation.
• Review stakeholder objectives and team's recommendations to ensure alignment and understanding.
• Drive analytics thought leadership and effectively contributes towards transformational initiatives.
• Ensure accuracy of data and deliverables of reporting employees with comprehensive policies and processes.

Understanding business objectives and developing models that help to achieve them,
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

• Experience with Big Data, Neural network (deep learning), and reinforcement learning • Ability to design machine learning systems • Research and implement appropriate ML algorithms and tools • Develop machine learning applications according to requirements • Select appropriate datasets and data representation methods • Run machine learning tests and experiments • Perform statistical analysis and fine-tuning using test results • Extend existing ML libraries and frameworks • Keep abreast of developments in the field • Understanding of data structures, data modeling and software architecture • Deep knowledge of math, probability, statistics and algorithms • Ability to write robust code in Python, Java and R Familiarity with machine learning frameworks (like Keras or PyTorch) and libraries (like scikit-learn)

Location: Gurgaon Role: • The person will be part of data science team. This person will be working on a close basis with the business analysts and the technology team to deliver the Data Science portion of the project and product. • Data Science contribution to a project can range between 30% to 80%. • Day to Day activities will include data exploration to solve a specific problem, researching of methods to be applied as solution, setting up ML process to be applied in context of a specific engagement/ requirement, contributing to building a DS platform, coding the solution, interacting with client on explanations, integration the DS solution with the technology solution, data cleaning and structuring etc. • Nature of work will depend on stage of a specific engagement, available engagements and individual skill At least 2-6 years of experience in: • Machine Learning (including deep learning methods): Algorithm design, analysis and development and performance improvement o Strong understanding of statistical and predictive modeling concepts, machine-learning approaches, clustering, classification, regression techniques, and recommendation (collaborative filtering) algorithms o Time Series Analysis o Optimization techniques and work experience with solvers for MILP and global optimization. • Data Science o Good experience in exploratory data analysis and feature design & development o Experience of applying and evaluating ML algorithms to practical predictive modeling scenarios in various verticals including (but not limited to) FMCG, Media, E-commerce and Hospitality. • Proficient with programming in Python (must have) & PySpark (good to have). Parallel ML algorithms design and development and usage for maximal performance on multi-core, distributed and/or GPU architectures. • Must be able to write a production ready code with reusable components and integration into data science platform. • Strong inclination to write structured code as per prevailing coding standards and best practices. • Ability to design a data science architecture for repeatability of solutions • Preparedness to manage whole cycle from data preparation to algorithm design to client presentation at individual level. • Comfort in working on AWS including managing data science AWS servers • Team player and good communication and interpersonal skills • Good experience in Natural Language Processing and its applications (Good to Have)

•Analytics, Big Data, Machine Learning (including deep learning methods): Algorithm design, analysis and development and performance improvement o Strong understanding of statistical and predictive modeling concepts, machine-learning approaches, clustering, classification, regression techniques, and recommendation (collaborative filtering) algorithms Share CV to me at

We are looking for a Machine Learning Developer who possesses apassion for machine technology & big data and will work with nextgeneration Universal IoT platform.Responsibilities:•Design and build machine that learns , predict and analyze data.•Build and enhance tools to mine data at scale• Enable the integration of Machine Learning models in Chariot IoTPlatform•Ensure the scalability of Machine Learning analytics across millionsof networked sensors•Work with other engineering teams to integrate our streaming,batch, or ad-hoc analysis algorithms into Chariot IoT's suite ofapplications•Develop generalizable APIs so other engineers can use our workwithout needing to be a machine learning expert

About the job: - You will work with data scientists to architect, code and deploy ML models - You will solve problems of storing and analyzing large scale data in milliseconds - architect and develop data processing and warehouse systems - You will code, drink, breathe and live python, sklearn and pandas. It’s good to have experience in these but not a necessity - as long as you’re super comfortable in a language of your choice. - You will develop tools and products that provide analysts ready access to the data About you: - Strong CS fundamentals - You have strong experience in working with production environments - You write code that is clean, readable and tested - Instead of doing it second time, you automate it - You have worked with some of the commonly used databases and computing frameworks (Psql, S3, Hadoop, Hive, Presto, Spark, etc) - It will be great if you have one of the following to share - a kaggle or a github profile - You are an expert in one or more programming languages (Python preferred). Also good to have experience with python-based application development and data science libraries. - Ideally, you have 2+ years of experience in tech and/or data. - Degree in CS/Maths from Tier-1 institutes.