Data Scientist

We are seeking an experienced Data Scientist with a proven track record in Machine Learning, Deep Learning, and a demonstrated focus on Large Language Models (LLMs) to join our cutting-edge Data Science team. You will play a pivotal role in developing and deploying innovative AI solutions that drive real-world impact to patients and healthcare providers.

Responsibilities

• LLM Development and Fine-tuning: fine-tune, customize, and adapt large language models (e.g., GPT, Llama2, Mistral, etc.) for specific business applications and NLP tasks such as text classification, named entity recognition, sentiment analysis, summarization, and question answering. Experience in other transformer-based NLP models such as BERT, etc. will be an added advantage.

• Data Engineering: collaborate with data engineers to develop efficient data pipelines, ensuring the quality and integrity of large-scale text datasets used for LLM training and fine-tuning

• Experimentation and Evaluation: develop rigorous experimentation frameworks to evaluate model performance, identify areas for improvement, and inform model selection. Experience in LLM testing frameworks such as TruLens will be an added advantage.

• Production Deployment: work closely with MLOps and Data Engineering teams to integrate models into scalable production systems.

• Predictive Model Design and Implementation: leverage machine learning/deep learning and LLM methods to design, build, and deploy predictive models in oncology (e.g., survival models)

• Cross-functional Collaboration: partner with product managers, domain experts, and stakeholders to understand business needs and drive the successful implementation of data science solutions

• Knowledge Sharing: mentor junior team members and stay up to date with the latest advancements in machine learning and LLMs

Qualifications Required

• Doctoral or master’s degree in computer science, Data Science, Artificial Intelligence, or related field

• 5+ years of hands-on experience in designing, implementing, and deploying machine learning and deep learning models

• 12+ months of in-depth experience working with LLMs. Proficiency in Python and NLP-focused libraries (e.g., spaCy, NLTK, Transformers, TensorFlow/PyTorch).

• Experience working with cloud-based platforms (AWS, GCP, Azure)

Additional Skills

• Excellent problem-solving and analytical abilities

• Strong communication skills, both written and verbal

• Ability to thrive in a collaborative and fast-paced environment

About CarWale: CarWale's mission is to bring delight in car buying, we offer a bouquet of reliable tools and services to help car consumers decide on buying the right car, at the right price and from the right partner. CarWale has always strived to serve car buyers and owners in the most comprehensive and convenient way possible. We provide a platform where car buyers and owners can research, buy, sell and come together to discuss and talk about their cars.We aim to empower Indian consumers to make informed car buying and ownership decisions with exhaustive and un-biased information on cars through our expert reviews, owner reviews, detailed specifications and comparisons. We understand that a car is by and large the second-most expensive asset a consumer associates his lifestyle with! Together with CarTrade & BikeWale, we are the market leaders in the personal mobility media space.About the Team:We are a bunch of enthusiastic analysts assisting all business functions with their data needs. We deal with huge but diverse datasets to find relationships, patterns and meaningful insights. Our goal is to help drive growth across the organization by creating a data-driven culture.

We are looking for an experienced Data Scientist who likes to explore opportunities and know their way around data to build world class solutions making a real impact on the business. 

Skills / Requirements –

• 3-5 years of experience working on Data Science projects
• Experience doing statistical modelling of big data sets
• Expert in Python, R language with deep knowledge of ML packages
• Expert in fetching data from SQL
• Ability to present and explain data to management
• Knowledge of AWS would be beneficial
• Demonstrate Structural and Analytical thinking
• Ability to structure and execute data science project end to end

Education –

Bachelor’s degree in a quantitative field (Maths, Statistics, Computer Science). Masters will be preferred.

• A Data and MLOps Engineering lead that has a good understanding of modern Data engineering frameworks with a focus on Microsoft Azure and Azure Machine Learning and its development lifecycle and DevOps.
• Aims to solve the problems encountered when turning Data into meaningful solutions using transformations and data science code into production Machine Learning systems. Some of these challenges include:
  • ML orchestration - how can I automate my ML workflows across multiple environments
  • Scalability - how can I take advantage of the huge computational power available in the cloud?
  • Serving - how can I make my ML models available to make predictions reliably when needed?
  • Monitoring - how can I effectively monitor my ML system in production to ensure reliability? Not just system metrics, but also get insight into how my models are performing over time
  • Reuse – how can I profess reuse of artefacts built and establish templates and patterns?

The MLOps team works closely with ML Engineering and DevOps teams. Rather than focus just on individual use cases, the focus would be to specialise in building the platforms and tools that can help adoption of MLOps across the organisation and develop best practices and ways of working to develop a state of the art MLOps capability.

A good understanding of AI/Machine Learning and software engineering best practices such as Cloud Engineering, Infrastructure-as-Code, and CI/CD.

Have excellent communication and consulting skills, while delivering innovative AI solutions on Azure.

Responsibilities will include:

• Building state-of-the-art MLOps platforms and tooling to help adoption of MLOps across organization
• Designing cloud ML architectures and provide a roadmap for flexible patterns
• Optimizing solutions for performance and scalability
• Leading and driving the evolving best practices for MLOps
• Helping to showcase expertise and leadership in this field

Tech stack

These are some of the tools and technologies that we use day to day. Key to success will be attitude and aptitude with a vision to build the next big thing in AI/ML field.

• Python - including poetry for dependency management, pytest for automated testing and fastapi for building APIs
• Microsoft Azure Platform - primarily focused on Databricks, Azure ML
• Containers
• CI/CD – Azure DevOps
• Strong programming skills in Python
• Solid understanding of cloud concepts
• Demonstrable interest in Machine Learning
• Understanding of IaC and CI/CD concepts
• Strong communication and presentation skills.

Remuneration: Best in the industry

Connect: https://www.linkedin.com/in/shweta-gupta-a361511

Roles and Responsibilities:

• Design, develop, and maintain the end-to-end MLOps infrastructure from the ground up, leveraging open-source systems across the entire MLOps landscape.
• Creating pipelines for data ingestion, data transformation, building, testing, and deploying machine learning models, as well as monitoring and maintaining the performance of these models in production.
• Managing the MLOps stack, including version control systems, continuous integration and deployment tools, containerization, orchestration, and monitoring systems.
• Ensure that the MLOps stack is scalable, reliable, and secure.

Skills Required:

• 3-6 years of MLOps experience
• Preferably worked in the startup ecosystem

Primary Skills:

• Experience with E2E MLOps systems like ClearML, Kubeflow, MLFlow etc.
• Technical expertise in MLOps: Should have a deep understanding of the MLOps landscape and be able to leverage open-source systems to build scalable, reliable, and secure MLOps infrastructure.
• Programming skills: Proficient in at least one programming language, such as Python, and have experience with data science libraries, such as TensorFlow, PyTorch, or Scikit-learn.
• DevOps experience: Should have experience with DevOps tools and practices, such as Git, Docker, Kubernetes, and Jenkins.

Secondary Skills:

• Version Control Systems (VCS) tools like Git and Subversion
• Containerization technologies like Docker and Kubernetes
• Cloud Platforms like AWS, Azure, and Google Cloud Platform
• Data Preparation and Management tools like Apache Spark, Apache Hadoop, and SQL databases like PostgreSQL and MySQL
• Machine Learning Frameworks like TensorFlow, PyTorch, and Scikit-learn
• Monitoring and Logging tools like Prometheus, Grafana, and Elasticsearch
• Continuous Integration and Continuous Deployment (CI/CD) tools like Jenkins, GitLab CI, and CircleCI
• Explain ability and Interpretability tools like LIME and SHAP

Be a part of the growth story of a rapidly growing organization in AI. We are seeking a passionate Machine Learning (ML) Engineer, with a strong background in developing and deploying state-of-the-art models on Cloud. You will participate in the complete cycle of building machine learning models from conceptualization of ideas, data preparation, feature selection, training, evaluation, and productionization.

On a typical day, you might build data pipelines, develop a new machine learning algorithm, train a new model or deploy the trained model on the cloud. You will have a high degree of autonomy, ownership, and influence over your work, machine learning organizations' evolution, and the direction of the company.

• Bachelor's degree in computer science/electrical engineering or equivalent practical experience
• 7+ years of Industry experience in Data Science, ML/AI projects. Experience in productionizing machine learning in the industry setting
• Strong grasp of statistical machine learning, linear algebra, deep learning, and computer vision
• 3+ years experience with one or more general-purpose programming languages including but not limited to: R, Python.
• Experience with PyTorch or TensorFlow or other ML Frameworks.
• Experience in using Cloud services such as AWS, GCP, Azure. Understand the principles of developing cloud-native application development

• Design and implement ML components, systems and tools to automate and enable our various AI industry solutions
• Apply research methodologies to identify the machine learning models to solve a business problem and deploy the model at scale.
• Own the ML pipeline from data collection, through the prototype development to production.
• Develop high-performance, scalable, and maintainable inference services that communicate with the rest of our tech stack

High Level Scope of Work :

• Work with AI / Analytics team to priorities MACHINE LEARNING Identified USE CASES for Development and Rollout
• Meet and understand current retail / Marketing Requirements and how AI/ML solution will address and automate the decision process.
• Develop AI/ML Programs using DATAIKU Solution & Python or open source tech with focus to deliver high Quality and accurate ML prediction Model
• Gather additional and external data sources to support the AI/ML Model as desired .
• Support the ML Model and FINE TUNEit to ensure high accuracy all the time.
• Example of use cases (Customer Segmentation , Product Recommendation, Price Optimization, Retail Customer Personalization Offers, Next Best Location for Business Est, CCTV Computer Vision, NLP and Voice Recognition Solutions)

Required technology expertise :

• Deep Knowledge & Understanding on MACHINE LEARNING ALGORITHMS (Supervised / Unsupervised Learning / Deep Learning Models)
• Hands on EXP for at least 5+ years with PYTHON and R STATISTICS PROGRAMMING Languages
• Strong Database Development knowledge using SQL and PL/SQL
• Must have EXP using Commercial Data Science Solution particularly DATAIKU and (Altryx, SAS, Azure ML, Google ML, Oracle ML is a plus)
• Strong hands on EXP with BIG DATA Solution Architecture and Optimization for AI/ML Workload.
• Data Analytics and BI Tools Hand on EXP particularly (Oracle OBIEE and Power BI)
• Have implemented and Developed at least 3 successful AI/ML Projects with tangible Business Outcomes In retail Focused Industry
• Have at least 5+ Years EXP in Retail Industry and Customer Focus Business.
• Ability to communicate with Business Owner & stakeholders to understand their current issues and provide MACHINE LEARNING Solution accordingly.

Qualifications

• Bachelor Degree or Master Degree in Data Science, Artificial Intelligent, Computer Science
• Certified as DATA SCIENTIST or MACHINE LEARNING Expert.

We are looking for a data scientist that will help us to discover the information hidden in vast amounts of data, and help us make smarter decisions to deliver even better products. Your primary focus will be in applying data mining techniques, doing statistical analysis, and building high quality prediction systems integrated with our products. 

• Selecting features, building and optimizing classifiers using machine learning techniques
• Data mining using state-of-the-art methods
• Extending company’s data with third party sources of information when needed
• Enhancing data collection procedures to include information that is relevant for building analytic systems
• Processing, cleansing, and verifying the integrity of data used for analysis
• Doing ad-hoc analysis and presenting results in a clear manner
• Creating automated anomaly detection systems and constant tracking of its performance

• Excellent understanding of machine learning techniques and algorithms, such as Linear regression, SVM, Decision Forests, LSTM, CNN etc.
• Experience with Deep Learning preferred.
• Experience with common data science toolkits, such as R, NumPy, MatLab, etc. Excellence in at least one of these is highly desirable
• Great communication skills
• Proficiency in using query languages such as SQL, Hive, Pig 
• Good applied statistics skills, such as statistical testing, regression, etc.
• Good scripting and programming skills 
• Data-oriented personality