12 Polars Jobs

Who You&aposll Work With Driving lasting impact and building long-term capabilities with our clients is not easy work. You are the kind of person who thrives in a high performance/high reward culture - doing hard things, picking yourself up when you stumble, and having the resilience to try another way forward. In return for your drive, determination, and curiosity, we&aposll provide the resources, mentorship, and opportunities you need to become a stronger leader faster than you ever thought possible. Your colleaguesat all levelswill invest deeply in your development, just as much as they invest in delivering exceptional results for clients. Every day, you&aposll receive apprenticeship, coaching, and exposure that will accelerate your growth in ways you wont find anywhere else. When you join us, you will have: Continuous learning: Our learning and apprenticeship culture, backed by structured programs, is all about helping you grow while creating an environment where feedback is clear, actionable, and focused on your development. The real magic happens when you take the input from others to heart and embrace the fast-paced learning experience, owning your journey. A voice that matters: From day one, we value your ideas and contributions. Youll make a tangible impact by offering innovative ideas and practical solutions. We not only encourage diverse perspectives, but they are critical in driving us toward the best possible outcomes. Global community: With colleagues across 65+ countries and over 100 different nationalities, our firms diversity fuels creativity and helps us come up with the best solutions for our clients. Plus, youll have the opportunity to learn from exceptional colleagues with diverse backgrounds and experiences. World-class benefits: On top of a competitive salary (based on your location, experience, and skills), we provide a comprehensive benefits package to enable holistic well-being for you and your family. Your Impact You will be developing PlanetView, a Software-as-a-Service platform which helps the financial sector understand and manage climate change risks and quantify carbon emissions. You will work alongside our physical and transition risk modelling teams, following agile processes, to bring analytical approaches and features to production. We work with financial data, terabytes of global climate data and a wide range of environmental, social and corporate governance (ESG) data and integrate them in our class-leading advanced economic models. In this role, you will be responsible to maintain and scale capabilities of Django, Django REST Framework based core application, and several backend microservices which are based on FastAPI and Pydantic. Youll have the opportunity to significantly influence the design of our backend processes. You will also manage your day-to-day priorities, time and commitments within your team setting while ensuring that technical standards and best practices are exercised. Lastly, you will apply new knowledge and innovation to the existing codebase. At Planetrics, you will be at the forefront of new technologies, applying best practices into development of PlanetView solution. You will deliver a real impact by identifying potential risks and capturing strategic opportunities of different climate-change policies and climate-related technologies worldwide. You will work in the environment that puts sustainability, diversity and digital transformation at the heart of what we do Your Qualifications and Skills Degree in Computer Science, Engineering, Mathematics, Quantitative Methods, or a related field. Proven track record of developing and maintaining production-level code. Strong proficiency in Python, with a focus on writing clean, efficient, and production-ready code. Deep expertise in building enterprise application using Django, Django REST Framework, FastAPI ,and Pydantic frameworks. Extensive experience with relational databases, SQL and Django ORM. Working knowledge of data analytics and visualisation Python libraries such as Pandas, Numpy, Polars, Plotly. Hands-on experience designing and implementing microservice architectures and distributed systems. Practical knowledge of AWS services such as EKS, RDS, Lambda, S3, DynamoDB, ElasticCache, SQS, AWS Batch and S3. Passion for automation, with experience in containerisation (e.g. Docker), shell scripting, and CI/CD pipelines, including GitHub actions. Solid understanding of software engineering best practices throughout the development lifecycle, including Agile methodologies, coding standards, peer code reviews, version control, build processes, testing, and deployment. Show more Show less

As a Data Engineering Lead, you will be responsible for designing, developing, and maintaining data pipelines using Python and related technologies. You will lead and mentor a team of data engineers, offering technical guidance and support. Collaboration with cross-functional teams to comprehend data requirements and deliver solutions will be a key aspect of your role. Implementing and managing data quality and validation processes will also be part of your responsibilities. You will work on optimizing data pipelines for enhanced performance and scalability, contributing to the establishment of data engineering best practices and standards. To be successful in this role, you should possess at least 6 years of Python development experience, with a preference for Python 3. Additionally, you should have a minimum of 2 years of experience in leading development teams. A strong working knowledge of Linux CLI environments is essential, along with expertise in data processing using Pandas or Polars. Proven experience in constructing data pipelines and familiarity with general data engineering practices are crucial. Proficiency in database technologies such as Snowflake and ORMs like SQLAlchemy is required. You should also be adept at developing REST APIs in Python, have a solid grasp of Python testing frameworks, and experience with Docker containerization of Python applications. Strong Git version control skills, excellent communication, and leadership abilities are indispensable for this role. Prior experience with Snowflake Database will be an added advantage.,

Department Profile From global institutions to hedge funds, investors come to Morgan Stanley for sales, trading, and market-making services in almost every type of financial instrument in all the worlds financial markets. Morgan Stanley professionals use our network and technology to provide liquidity and sophisticated analysis, to manage risk and execute reliably in the fast-changing markets. Morgan Stanleys Institutional Equity Division (IED) is a world leader in the origination, distribution and trading of equity, equity-linked and equity-derivative securities. Our broad and deep client relationships, market-leading platform and intellectual insights enable us to be a world-class service provider to our clients for their financing, market access and portfolio management needs. Global Markets Group is the offshoring arm of Morgan Stanleys Equity businesses in India. It covers functions across IED ranging from those associated with sales, trading, analytics, Strats to risk management. The Quantitative Research (QR) group designs, builds and maintains the models which drive the equity trading engines at Morgan Stanley. Our systems are used globally by both internal trading groups and clients of the firm. We utilize systematic, data-driven approaches to understand how markets work and put those ideas in action. The team spans the disciplines of finance, econometrics, statistics, mathematics, machine learning and data analysis, with many team members well versed in multiple areas. We are looking to hire highly talented, creative individuals who are enthusiastic about research; and enthusiastic about contributing to a leading-edge team, in an intellectually stimulating environment. Primary Responsibilities This role, based in Mumbai, requires the individual to work with global Morgan Stanley Quantitative Research teams. The successful candidate will be a fast-learning, dynamic, pro-active and self-motivated individual who can assist the team in maintaining and analyzing referential data, as well as generating ad hoc performance and market condition reports for clients. The expected working hours will be 7:30 am (local time) to 4:30 pm (local time) What Youll Do In The Role Analyze events related to index rebalances, including flow estimation, quantitative and qualitative assessments, and reporting. Design and implement efficient data processing pipeline using modern Python frameworks. Onboarding and analyze data from various internal and external sources. Prepare scenario analyses and historical performance backtests for potential index events. Investigate market data, pricing and analytics issues. Simplification, automation, and support of existing manual processes. Drive continuous improvement in development practices. What Youll Bring To The Role A degree in quantitative discipline (e.g., BE, BTech, MS in Mathematics, Statistics, Financial Engineering, or Economics). 7+ years of hands-on experience with Python (mandatory). Strong working knowledge of Linux CLI environment. Strong expertise in data processing with Pandas/Polars/Numpy. Proven experience in building data pipelines. Experience with large data sets and SQL for data processing. Strong analytical skills with a solid understanding of statistical and financial concepts. Strong written and verbal communication skills, with the ability to articulate ideas clearly to a non-technical audience. Strong organizational skills with the ability to multitask and meet tight deadlines. Exceptional attention to detail. Good To Have Knowledge of index rebalances, funds, ETFs, and related mechanisms. Experience with market data vendors Bloomberg, Refinitiv etc. Experience working in the finance industry, demonstrable curiosity in quantitative research and investment. What You Can Expect From Morgan Stanley We are committed to maintaining the first-class service and high standard of excellence that have defined Morgan Stanley for over 89 years. Our values - putting clients first, doing the right thing, leading with exceptional ideas, committing to diversity and inclusion, and giving back - arent just beliefs, they guide the decisions we make every day to do what&aposs best for our clients, communities and more than 80,000 employees in 1,200 offices across 42 countries. At Morgan Stanley, youll find an opportunity to work alongside the best and the brightest, in an environment where you are supported and empowered. Our teams are relentless collaborators and creative thinkers, fueled by their diverse backgrounds and experiences. We are proud to support our employees and their families at every point along their work-life journey, offering some of the most attractive and comprehensive employee benefits and perks in the industry. Theres also ample opportunity to move about the business for those who show passion and grit in their work. To learn more about our offices across the globe, please copy and paste https://www.morganstanley.com/about-us/global-offices into your browser. Morgan Stanley is an equal opportunities employer. We work to provide a supportive and inclusive environment where all individuals can maximize their full potential. Our skilled and creative workforce is comprised of individuals drawn from a broad cross section of the global communities in which we operate and who reflect a variety of backgrounds, talents, perspectives, and experiences. Our strong commitment to a culture of inclusion is evident through our constant focus on recruiting, developing, and advancing individuals based on their skills and talents. Show more Show less

As a Backend Developer, your primary responsibility will be to develop and maintain backend services using Python, with a strong emphasis on FastAPI, NumPy, and Polars for efficient handling of data. You will be tasked with building and managing agentic workflows utilizing LangChain, LangGraph, and MCP Agents to facilitate dynamic, multi-step reasoning. Additionally, you will design and execute RAG pipelines for contextual information retrieval and response generation. Integration and optimization of MongoDB or similar vector databases like FAISS and Pinecone for semantic search and embedding storage will also fall under your purview. Collaboration with cross-functional teams to deploy scalable AI services in production will be a crucial part of your role. Furthermore, you will be responsible for conducting performance tuning, testing, and deployment of AI components, while also keeping abreast of the latest developments in GenAI, LLMs, and agentic architectures. The ideal candidate for this position should possess a minimum of 3-6 years of experience in backend development using Python. You should have hands-on experience with FastAPI for constructing RESTful APIs, as well as proficiency in NumPy and Polars for numerical and tabular data processing. A solid understanding of Generative AI concepts is essential, along with practical experience in working with LangChain, LangGraph, and MCP Agents. Experience in building and deploying agentic RAG systems and familiarity with MongoDB or other vector databases for semantic search and retrieval will be advantageous. Knowledge of cloud platforms such as Azure and containerization tools like Docker/Kubernetes will be considered a plus. To qualify for this role, you should hold a Bachelors or Masters degree in computer science, data science, mathematics, or a related field.,

Job Title: Python Developer (38 Years Experience) Location: Chennai Job Type: Full-Time Work Mode: Office (5 Days) Experience Required: 3 to 8 Years Job Description Ability to perform data transformations using Python, pandas, numpy, polars. Ability to query data from SQL and NoSQL databases. For SQL: Given a database schema should be able to create a query to extract desired data. For NoSQL: Experience performing hierarchical queries in REST or experience with GraphQL. Database operation (indexing etc), cache (redis etc), data management, handle missing data etc. Data visualization in Python (Plotly, Bokeh, matplotlib etc.) Some experience with distributed programming using Spark or Dask or similar toolkits that can take sequential code and run it across multiple processes. Familiar with machine learning, experience with deep learning model analysis, popular architectures, augmentations, fine tune, boosting, dimension reduction etc. Basic knowledge of computer vision and image processing, understand concept of feature extraction, object detection and classification, segmentation, denoise, super resolution etc. Familiar with python / tensorflow / pytorch / openCV etc. Good software skill, knows concept and object-oriented design, and basic software system design Experience of organize and aggregate large datasets Good data analysis and analytic skill

Backend Developer Database PostgreSQL PostGIS:For all PostgreSQLpsycopg2 asyncpg PostgreSQL adapters PythonGDAL OGR via osgeo module T Pandas, PAWS S3/RDS/EC2 olars tabular data manipulation, NumPy Django and Django REST GeoJSON, ShapefileGeoTIFF

Good knowledge of building Data Pipelines using Python with Flask API and library Polars and strong knowledge of relational databases like MySQL, DB2 and Mssql server and non relational databases MongoDB. Knowledge of Kafka is add on. Stack: 1. Python 2. Polars 3. MySQL, DB2 and Mssql server databases 4. MongoDB. 5. Very Good Communication skills. 6. Open to travel to USA

Good knowledge of building Data Pipelines using Python with Flask API and library Polars and strong knowledge of relational databases like MySQL, DB2 and Mssql server and non relational databases MongoDB. Knowledge of Kafka is add on. Stack: 1. Python 2. Polars 3. MySQL, DB2 and Mssql server databases 4. MongoDB. 5. Very Good Communication skills. 6. Open to travel to USA

Job Responsibilities: To transition legacy Rules from Python using the Polars Library to SparkSQL To create new Rules using SparkSQL based on written requirements. Must Have Skills: Understanding of Polars library Understanding of SparkSQL (this is more important than Polars) Good English communication Ability to work in a collaborative environment Experience with US healthcare data preferred Understanding of SparkSQL (this is more important than Polars)

Skills -Pydantic, Python, SQl, Fast API Mail your resume with salary details: current CTC: Expected CTC: Notice Period: cynthia.s@noblq.com whatsapp -9677090220

Strong in Python and experience with Jupyter notebooks, Python packages like polars, pandas, numpy, scikit-learn, matplotlib, etc. Must have: Experience with machine learning lifecycle, including data preparation, training, evaluation, and deployment Must have: Hands-on experience with GCP services for ML & data science Must have: Experience with Vector Search and Hybrid Search techniques Must have: Experience with embeddings generation using models like BERT, Sentence Transformers, or custom models Must have: Experience in embedding indexing and retrieval (e.g., Elastic, FAISS, ScaNN, Annoy) Must have: Experience with LLMs and use cases like RAG (Retrieval-Augmented Generation) Must have: Understanding of semantic vs lexical search paradigms Must have: Experience with Learning to Rank (LTR) techniques and libraries (e.g., XGBoost, LightGBM with LTR support) Should be proficient in SQL and BigQuery for analytics and feature generation Should have experience with Dataproc clusters for distributed data processing using Apache Spark or PySpark Should have experience deploying models and services using Vertex AI, Cloud Run, or Cloud Functions Should be comfortable working with BM25 ranking (via Elasticsearch or OpenSearch) and blending with vector-based approaches Good to have: Familiarity with Vertex AI Matching Engine for scalable vector retrieval Good to have: Familiarity with TensorFlow Hub, Hugging Face, or other model repositories Good to have: Experience with prompt engineering, context windowing, and embedding optimization for LLM-based systems Should understand how to build end-to-end ML pipelines for search and ranking applications Must have: Awareness of evaluation metrics for search relevance (e.g., precision@k, recall, nDCG, MRR) Should have exposure to CI/CD pipelines and model versioning practices GCP Tools Experience: ML & AI: Vertex AI, Vertex AI Matching Engine, AutoML, AI Platform Storage: BigQuery, Cloud Storage, Firestore Ingestion: Pub/Sub, Cloud Functions, Cloud Run Search: Vector Databases (e.g., Matching Engine, Qdrant on GKE), Elasticsearch/OpenSearch Compute: Cloud Run, Cloud Functions, Vertex Pipelines, Cloud Dataproc (Spark/PySpark) CI/CD & IaC: GitLab/GitHub Actions Location: Remote- Bengaluru,Hyderabad,Delhi / NCR,Chennai,Pune,Kolkata,Ahmedabad,Mumbai

Expert in Python, with knowledge of at least one Python web framework such as Flask, FAST, Django etc. Knowledge and experience on using Python libraries like Numpy, Pandas, Polars, Dask. Familiarity with some ORM (Object Relational Mapper) libraries. Familiarity with Relational and/or No-SQL databases. Proficient in using editors like VS Code, Eclipse, PyCharm, PyScripter etc. Understanding of fundamental design principles behind a scalable application. Strong unit test and debugging skills. Proficient understanding of code versioning tools such as Git, Mercurial or SVN. Basic understanding of front-end technologies, such as JavaScript, HTML5, and CSS3. Knowledge of Kafka would be a huge plus.