As an Associate Manager - Senior Data scientist you will solve some of the most impactful business problems for our clients using a variety of AI and ML technologies. You will collaborate with business partners and domain experts to design and develop innovative solutions on the data to achieve
predefined outcomes.
• Engage with clients to understand current and future business goals and translate business
problems into analytical frameworks
• Develop custom models based on an in-depth understanding of underlying data, data structures,
and business problems to ensure deliverables meet client needs
• Create repeatable, interpretable and scalable models
• Effectively communicate the analytics approach and insights to a larger business audience
• Collaborate with team members, peers and leadership at Tredence and client companies
Qualification:
1. Bachelor's or Master's degree in a quantitative field (CS, machine learning, mathematics,
statistics) or equivalent experience.
2. 5+ years of experience in data science, building hands-on ML models
3. Experience leading the end-to-end design, development, and deployment of predictive
modeling solutions.
4. Excellent programming skills in Python. Strong working knowledge of Python’s numerical, data
analysis, or AI frameworks such as NumPy, Pandas, Scikit-learn, Jupyter, etc.
5. Advanced SQL skills with SQL Server and Spark experience.
6. Knowledge of predictive/prescriptive analytics including Machine Learning algorithms
(Supervised and Unsupervised) and deep learning algorithms and Artificial Neural Networks
7. Experience with Natural Language Processing (NLTK) and text analytics for information
extraction, parsing and topic modeling.
8. Excellent verbal and written communication. Strong troubleshooting and problem-solving skills.
Thrive in a fast-paced, innovative environment
9. Experience with data visualization tools — PowerBI, Tableau, R Shiny, etc. preferred
10. Experience with cloud platforms such as Azure, AWS is preferred but not required
Similar jobs
• 6+ years of data science experience.
• Demonstrated experience in leading programs.
• Prior experience in customer data platforms/finance domain is a plus.
• Demonstrated ability in developing and deploying data-driven products.
• Experience of working with large datasets and developing scalable algorithms.
• Hands-on experience of working with tech, product, and operation teams.
Technical Skills:
• Deep understanding and hands-on experience of Machine learning and Deep
learning algorithms. Good understanding of NLP and LLM concepts and fair
experience in developing NLU and NLG solutions.
• Experience with Keras/TensorFlow/PyTorch deep learning frameworks.
• Proficient in scripting languages (Python/Shell), SQL.
• Good knowledge of Statistics.
• Experience with big data, cloud, and MLOps.
Soft Skills:
• Strong analytical and problem-solving skills.
• Excellent presentation and communication skills.
• Ability to work independently and deal with ambiguity.
Continuous Learning:
• Stay up to date with emerging technologies.
Qualification.
A degree in Computer Science, Statistics, Applied Mathematics, Machine Learning, or any related field / B. Tech.
Responsibilities:
- Data science model review, run the code refactoring and optimization, containerization, deployment, versioning, and monitoring of its quality.
- Design and implement cloud solutions, build MLOps on the cloud (preferably AWS)
- Work with workflow orchestration tools like Kubeflow, Airflow, Argo, or similar tools
- Data science models testing, validation, and test automation.
- Communicate with a team of data scientists, data engineers, and architects, and document the processes.
Eligibility:
- Rich hands-on experience in writing object-oriented code using python
- Min 3 years of MLOps experience (Including model versioning, model and data lineage, monitoring, model hosting and deployment, scalability, orchestration, continuous learning, and Automated pipelines)
- Understanding of Data Structures, Data Systems, and software architecture
- Experience in using MLOps frameworks like Kubeflow, MLFlow, and Airflow Pipelines for building, deploying, and managing multi-step ML workflows based on Docker containers and Kubernetes.
- Exposure to deep learning approaches and modeling frameworks (PyTorch, Tensorflow, Keras, etc. )
Location: Chennai
Education: BE/BTech
Experience: Minimum 3+ years of experience as a Data Scientist/Data Engineer
Domain knowledge: Data cleaning, modelling, analytics, statistics, machine learning, AI
Requirements:
- To be part of Digital Manufacturing and Industrie 4.0 projects across client group of companies
- Design and develop AI//ML models to be deployed across factories
- Knowledge on Hadoop, Apache Spark, MapReduce, Scala, Python programming, SQL and NoSQL databases is required
- Should be strong in statistics, data analysis, data modelling, machine learning techniques and Neural Networks
- Prior experience in developing AI and ML models is required
- Experience with data from the Manufacturing Industry would be a plus
Roles and Responsibilities:
- Develop AI and ML models for the Manufacturing Industry with a focus on Energy, Asset Performance Optimization and Logistics
- Multitasking, good communication necessary
- Entrepreneurial attitude
Additional Information:
- Travel: Must be willing to travel on shorter duration within India and abroad
- Job Location: Chennai
- Reporting to: Team Leader, Energy Management System
Job brief
We are looking for a Data Scientist to analyze large amounts of raw information to find patterns that will help improve our company. We will rely on you to build data products to extract valuable business insights.
In this role, you should be highly analytical with a knack for analysis, math and statistics. Critical thinking and problem-solving skills are essential for interpreting data. We also want to see a passion for machine-learning and research.
Your goal will be to help our company analyze trends to make better decisions.
Requirements
1. 2 to 4 years of relevant industry experience
2. Experience in Linear algebra, statistics & Probability skills, such as distributions, Deep Learning, Machine Learning
3. Strong mathematical and statistics background is a must
4. Experience in machine learning frameworks such as Tensorflow, Caffe, PyTorch, or MxNet
5. Strong industry experience in using design patterns, algorithms and data structures
6. Industry experience in using feature engineering, model performance tuning, and optimizing machine learning models
7. Hands on development experience in Python and packages such as NumPy, Sci-Kit Learn and Matplotlib
8. Experience in model building, hyper
with the engineering team to strategize and execute the development of data products
● Execute analytical experiments methodically to help solve various problems and make a true impact across
various domains and industries
NLP ENGINEER at KARZA TECHNOLOGIES
● Identify relevant data sources and sets to mine for client business needs, and collect large structured and
unstructured datasets and variables
● 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
● Analyze data for trends and patterns, and Interpret data with a clear objective in mind
● Implement analytical models into production by collaborating with software developers and machine
learning engineers
● Communicate analytic solutions to stakeholders and implement improvements as needed to operational
systems
What you need to work with us:
● Good understanding of data structures, algorithms, and the first principles of mathematics.
● Proficient in Python and using packages like NLTK, Numpy, Pandas
● Should have worked on deep learning frameworks (like Tensorflow, Keras, PyTorch, etc)
● Hands-on experience in Natural Language Processing, Sequence, and RNN Based models
● Mathematical intuition of ML and DL algorithms
● Should be able to perform thorough model evaluation by creating hypotheses on the basis of statistical
analyses
● Should be comfortable in going through open-source code and reading research papers.
● Should be curious or thoughtful enough to answer the “WHYs” pertaining to the most cherished
observations, thumb rules, and ideas across the data science community.
Qualification and Experience Required:
● 1 - 4 years of relevant experience
● Bachelor/ Master’s degree in computer science / Computer Engineering / Information Technology
- 4+ years of experience Solid understanding of Python, Java and general software development skills (source code management, debugging, testing, deployment etc.).
- Experience in working with Solr and ElasticSearch Experience with NLP technologies & the handling of unstructured text Detailed understanding of text pre-processing and normalisation techniques such as tokenisation, lemmatisation, stemming, POS tagging etc.
- Prior experience in implementation of traditional ML solutions - classification, regression or clustering problem Expertise in text-analytics - Sentiment Analysis, Entity Extraction, Language modelling - and associated sequence learning models ( RNN, LSTM, GRU).
- Comfortable working with deep-learning libraries (eg. PyTorch)
- Candidate can even be a fresher with 1 or 2 years of experience IIIT, IIIT, Bits Pilani, top 5 local colleges are preferred colleges and universities.
- A Masters candidate in machine learning.
- Can source candidates from Mu Sigma and Manthan.
Hammoq Inc is a rapidly growing startup in the reselling sector. Our app provides product listings, cross-platform data analytics, and Cross-platform delisting as our core services.
Launched Web app in 2020 and iOS app at the start of 2021, we are continuing our exponential growth, and we were hoping you could play a core role in our mission.
Hammoq is looking for a Senior ML/Machine Vision Architect / Researcher, an expert in Deep Learning, to join our passionate developers' team to create our unique SaaS web app.
The ideal candidate will be responsible for developing new Machine Learning / Machine vision models according to the business needs.
*What you'll do
- You’ll lead the ML R&D process at Hammoq.
- You will build ML architectures to optimise the process.
- You'll collaborate with our hardworking, nimble, and supportive team through daily standups, company presentations, product demos, slack discussions
- You'll work on solving machine vision / Machine Learning problems and implementations.
- You'll use ML libraries of IOS and Android to build and run models on the mobile devices
Skills and expertise that will help you succeed
- Must have experience working with OpenCV, TensorFlow, and Keras environment
- Must have the ability to develop your own models.
- Working experience of training and deploying computer vision models
- Experience in Computer Vision and Machine Learning (including Deep Learning) algorithms.
- Experience in image analytics - including feature extraction, object detection, classification, and tracking
- Experience in image manipulation
- PhD in Computer Vision , Machine Learning, Machine Vision or any related field is a must.
- Strong programming skills in Python, including NumPy, Scikit Learn, Pandas, and Matplotlib
- Self-governing analytical problem-solving skills for efficient and uninterrupted development of solutions
- Strong communications skills for an adequate description of technical concepts to others
Nice to have
- Experience in building APIs implementing ML models
- Knowledge or basic understanding of any Cloud ML technologies or Cloud ML service providers.
- Experience in the e-commerce industry
- Data & Analytics team is responsible to integrate new data sources and build data models, data dictionaries and machine learning models for the Wholesale Bank.
- The goal is to design and build data products to support squads in Wholesale Bank with business outcomes and development of business insights. In this Job Family we make a distinction between Data Analysts and Data Scientist. Both scientists as analysts work with data and are expected to write queries, work with engineering teams to source the right data, perform data munging (getting data into the correct format, convenient for analysis/interpretation) and derive information from data.
- The data analyst typically works on simpler structured SQL or similar databases or with other BI tools/packages. The Data Scientists are expected to build statistical models or be hands-on in machine learning and advanced programming.
- Role of Data Scientist to support our Corporate banking teams with insights gained from analyzing company data. The ideal candidate is adept at using 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 strong experience 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 have banking or corporate banking experience.
6 Years - 10 Years
Analytics
- Should be comfortable in solving Wholesale Banking domain analytical solution within AI/ML platform