Data Scientist

• Bring in industry best practices around creating and maintaining robust data pipelines for complex data projects with/without AI component
  • programmatically ingesting data from several static and real-time sources (incl. web scraping)
  • rendering results through dynamic interfaces incl. web / mobile / dashboard with the ability to log usage and granular user feedbacks
  • performance tuning and optimal implementation of complex Python scripts (using SPARK), SQL (using stored procedures, HIVE), and NoSQL queries in a production environment

• Industrialize ML / DL solutions and deploy and manage production services; proactively handle data issues arising on live apps
• Perform ETL on large and complex datasets for AI applications - work closely with data scientists on performance optimization of large-scale ML/DL model training
• Build data tools to facilitate fast data cleaning and statistical analysis
• Ensure data architecture is secure and compliant
• Resolve issues escalated from Business and Functional areas on data quality, accuracy, and availability
• Work closely with APAC CDO and coordinate with a fully decentralized team across different locations in APAC and global HQ (Paris).

•  Expert in structured and unstructured data in traditional and Big data environments – Oracle / SQLserver, MongoDB, Hive / Pig, BigQuery, and Spark
• Have excellent knowledge of Python programming both in traditional and distributed models (PySpark)
• Expert in shell scripting and writing schedulers
• Hands-on experience with Cloud - deploying complex data solutions in hybrid cloud / on-premise environment both for data extraction/storage and computation
• Hands-on experience in deploying production apps using large volumes of data with state-of-the-art technologies like Dockers, Kubernetes, and Kafka
• Strong knowledge of data security best practices
• 5+ years experience in a data engineering role
• Science / Engineering graduate from a Tier-1 university in the country
• And most importantly, you must be a passionate coder who really cares about building apps that can help people do things better, smarter, and faster even when they sleep

• NLP 

• ML programming
• Spark
• Model Deployment
• Experience processing unstructured data and building NLP models
• Experience with big data tools pyspark
• Pipeline orchestration using Airflow and model deployment experience is preferred

THE IDEAL CANDIDATE WILL

• Engage with executive level stakeholders from client's team to translate business problems to high level solution approach
• Partner closely with practice, and technical teams to craft well-structured comprehensive proposals/ RFP responses clearly highlighting Tredence’s competitive strengths relevant to Client's selection criteria
• Actively explore the client’s business and formulate solution ideas that can improve process efficiency and cut cost, or achieve growth/revenue/profitability targets faster
• Work hands-on across various MLOps problems and provide thought leadership
• Grow and manage large teams with diverse skillsets
• Collaborate, coach, and learn with a growing team of experienced Machine Learning Engineers and Data Scientists

ELIGIBILITY CRITERIA

• BE/BTech/MTech (Specialization/courses in ML/DS)
• At-least 7+ years of Consulting services delivery experience
• Very strong problem-solving skills & work ethics
• Possesses strong analytical/logical thinking, storyboarding and executive communication skills
• 5+ years of experience in Python/R, SQL
• 5+ years of experience in NLP algorithms, Regression & Classification Modelling, Time Series Forecasting
• Hands on work experience in DevOps
• Should have good knowledge in different deployment type like PaaS, SaaS, IaaS
• Exposure on cloud technologies like Azure, AWS or GCP
• Knowledge in python and packages for data analysis (scikit-learn, scipy, numpy, pandas, matplotlib).
• Knowledge of Deep Learning frameworks: Keras, Tensorflow, PyTorch, etc
• Experience with one or more Container-ecosystem (Docker, Kubernetes)
• Experience in building orchestration pipeline to convert plain python models into a deployable API/RESTful endpoint.
• Good understanding of OOP & Data Structures concepts

Nice to Have:

• Exposure to deployment strategies like: Blue/Green, Canary, AB Testing, Multi-arm Bandit
• Experience in Helm is a plus
• Strong understanding of data infrastructure, data warehouse, or data engineering

You can expect to –

• Work with world’ biggest retailers and help them solve some of their most critical problems. Tredence is a preferred analytics vendor for some of the largest Retailers across the globe
• Create multi-million Dollar business opportunities by leveraging impact mindset, cutting edge solutions and industry best practices.
• Work in a diverse environment that keeps evolving
• Hone your entrepreneurial skills as you contribute to growth of the organization

Job Responsibilities:-

• Develop robust, scalable and maintainable machine learning models to answer business problems against large data sets.
• Build methods for document clustering, topic modeling, text classification, named entity recognition, sentiment analysis, and POS tagging.
• Perform elements of data cleaning, feature selection and feature engineering and organize experiments in conjunction with best practices.
• Benchmark, apply, and test algorithms against success metrics. Interpret the results in terms of relating those metrics to the business process.
• Work with development teams to ensure models can be implemented as part of a delivered solution replicable across many clients.
• Knowledge of Machine Learning, NLP, Document Classification, Topic Modeling and Information Extraction with a proven track record of applying them to real problems.
• Experience working with big data systems and big data concepts.
• Ability to provide clear and concise communication both with other technical teams and non-technical domain specialists.
• Strong team player; ability to provide both a strong individual contribution but also work as a team and contribute to wider goals is a must in this dynamic environment.
• Experience with noisy and/or unstructured textual data.

knowledge graph and NLP including summarization, topic modelling etc

• Strong coding ability with statistical analysis tools in Python or R, and general software development skills (source code management, debugging, testing, deployment, etc.)
• Working knowledge of various text mining algorithms and their use-cases such as keyword extraction, PLSA, LDA, HMM, CRF, deep learning & recurrent ANN, word2vec/doc2vec, Bayesian modeling.
• Strong understanding of text pre-processing and normalization techniques, such as tokenization,
• POS tagging and parsing and how they work at a low level.
• Excellent problem solving skills.
• Strong verbal and written communication skills
• Masters or higher in data mining or machine learning; or equivalent practical analytics / modelling experience
• Practical experience in using NLP related techniques and algorithms
• Experience in open source coding and communities desirable.

Able to containerize Models and associated modules and work in a Microservices environment

Hi All,

We are hiring Data Engineer for one of our client for Bangalore & Chennai Location.


Strong Knowledge of SCCM, App V, and Intune infrastructure.

Powershell/VBScript/Python,

Windows Installer

Knowledge of Windows 10 registry

Application Repackaging

Application Sequencing with App-v

Deploying and troubleshooting applications, packages, and Task Sequences.

Security patch deployment and remediation

Windows operating system patching and defender updates

Thanks,
Mohan.G

• Proficient in R and Python
• Work experience 1+ years with at least 6 months working with Python
• Prior experience with building ML models
• Prior experience with SQL
• Knowledge of statistical techniques
• Experience with working on Spatial Data will be an added advantage