Key Responsibilities: <ul><li>Proven experience (typically 4+ years) in data science.</li><li>Machine learning and NLP Skills</li><li>Model Deployment Skills</li><li>SQL programming and JIRA practices</li><li>Gen-AI (Prompt Engineering and LLM fine tuning) good to have</li><li>Python skills needed</li><li>Web app dev experience would be great</li><li>Very strong communication (written & verbal) required to work closely & within groups effectively</li><li>Should require minimum support – someone proactive, takes initiative & will hit the ground running</li><li>Experience with metric development</li><li>Exposure to dash and plotly python packages</li><li>Strong communication skills, with the ability to explain complex technical concepts to non-technical stakeholders.</li><li>Proven track record of managing, mentoring, and growing a team of data scientists and analysts.</li><li>Experience working in an Agile environment and managing cross-functional teams to deliver on-time, high-quality projects.</li><li>Experience in business strategy and understanding of how data science drives company-wide initiatives.</li><li>Strong project management skills, including the ability to prioritize, scope, and execute complex projects.</li></ul>

About InfoNet:InfoNet is a forward-thinking technology solutions provider committed to harnessing data to drive innovation. We specialize in creating impactful data-driven solutions, and we’re looking for a talented Senior Data Scientist to join our team. If you’re passionate about leveraging AI/ML techniques, have experience with cutting-edge tools like LLMs, and want to work in a collaborative environment, we’d love to hear from you! Job Description:As a Senior Data Scientist at InfoNet, you will work on projects that involve analyzing data, building machine learning models, and developing AI-driven solutions. This role requires a solid understanding of AI/ML techniques, knowledge of advanced technologies like Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG), and proficiency in Python programming. You will also contribute to creating intuitive data tools using frameworks like Streamlit. Key Responsibilities:<ul><li>Data Analysis & Insights: Perform exploratory data analysis (EDA) and apply statistical techniques to derive actionable insights.</li><li>AI/ML Modeling: Develop machine learning models using techniques such as clustering, regression, and classification.</li><li>LLM Expertise: Work on projects involving Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) to solve real-world problems.</li><li>Statistical Modeling: Apply basic statistical methods (mean, median, mode, standard deviation, etc.) to analyze and interpret data.</li><li>Tool Development: Build interactive and user-friendly data applications using Python packages like Streamlit.</li><li>Collaboration: Work closely with cross-functional teams including data engineers, software developers, and product managers.</li><li>Documentation: Prepare detailed documentation for models, data pipelines, and methodologies.</li></ul> Qualifications:<ul><li>Educational Background: Bachelor’s or Master’s degree in Data Science, Statistics, Computer Science, or a related field.</li><li>Experience: 4+ years of experience in data science, machine learning, or a related role.</li><li>AI/ML Skills: Strong understanding of machine learning techniques such as clustering and regression.</li><li>LLM Knowledge: Experience or knowledge of Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG).</li><li>Statistics Proficiency: Solid grasp of statistical concepts, including mean, median, mode, variance, and standard deviation.</li><li>Python Expertise: Proficiency in Python and libraries such as scikit-learn, pandas, numpy, matplotlib, and Streamlit.</li><li>Problem-Solving Skills: Ability to apply data-driven solutions to complex business problems.</li><li>Communication: Strong verbal and written communication skills to present findings to non-technical stakeholders.</li></ul> What We Offer:<ul><li>Remote Work Flexibility: Work remotely from anywhere with occasional team meetups in Gurugram.</li><li>Competitive Compensation: Attractive salary package based on experience and skills.</li><li>Learning Opportunities: Access to professional development resources and cutting-edge projects.</li><li>Collaborative Environment: Be part of a dynamic, innovative team that values knowledge sharing.</li></ul>

Location: GurugramWork Mode: 5 Days (WFO) Requirements:• 5+ years of industry experience in taking research prototypes to production.• Strong expertise in data analytics and interpretation skills.• Proven ability to design analytical solutions to complex business problems and to partner with cross-functional peers to tailor those solutions for the greatest possible impact.• Deep understanding of ML domains (e.g. classification algorithms, NLP, computer vision, recommendation, anomaly detection, graph learning), algorithms (eg. deep learning, gradient boosted trees, optimization), and best practices, (e.g. skew minimization, A/B testing, feature engineering, model selection)• Strong programming (Python / Scala) or data engineering skills.• Utilize OSS ML technologies such as PyTorch, TensorFlow, Spark, and Airflow.• Versatility to communicate clearly with both technical and non-technical audiences.• Publications or presentations in recognized Machine Learning and Data Mining journals/conferences are a plus.

What You’ll Do● Support business decision making by deriving actionable insightsfrom structured and unstructured data● Conduct end-to-end machine learning and data analyticsactivities, including data wrangling, feature engineering, buildingand evaluating ML models.● Research and implement novel machine learning approaches to enable informedbusiness decisions.● Collaborate with business and engineering teams to analyze, extract,normalize, and label relevant data.● Perform data engineering, feature engineering, datapreprocessing to train and tune ML models● Utilize BI tools to prepare reports, analyze and visualize data.● Implement MLOps practices such as CI/CD and continuous training(CT) for deploying and maintaining ML models in productionenvironments.Your Superpowers:● Experience○ 3 to 5 years of experience in data analytics and machine learning○ Hands-on experience with ML frameworks and libraries such as TensorFlow, PyTorch,Scikit-learn, Pandas and NumPy.○ Proficiency in writing production-quality code in Python, with a strongunderstanding of object-oriented programming principles○ Proven experience in analyzing and working with large datasets○ Hands on experience with various BI tools○ Expertise in applying both supervised and unsupervised learning techniques 3 ● Expertise & Learning Agility○ You are open to new ways of thinking and committed to acquiring new skills toretain a competitive advantage○ You employ a thoughtful process of analyzing data and problem solving to reachwell-reasoned solutions● Strong collaboration, communication, and creative thinking skills Join Electrifi

What drives us? Imagine: a single tap on your phone unlocks a world that transforms your entire car ownership journey, covering every milestone - from finding your perfect match to keeping it running smoothly, to selling it later. That's the future we're building at CARS24 Financial Services. Our mission is to ensure car ownership is stress-free. We want our customers to focus on the open road, not roadside worries. We're building a one stop shop - a Super App for all their car needs, powered by technology, data science, and deep customer insights, We are already one of the largest Autotech companies in the world, but we are not stopping here. We aim to grow 10x in the next five years. What will you drive? As a member of Collection Models Data Science team, you would be focused on gathering, analyzing, and utilizing data to improve collections, whether for debt recovery, customer engagement, or business insights. You will be exposed to activities ranging from (but not limiting to) model development, evaluation, validation, monitoring, implementation testing and documentation. You will have an opportunity to learn industry best practices in credit models development and will also be working on experimental models using machine learning techniques. You will also own the models and be a SPOC for all assessment by Risk Management team. Essential Responsibilities: <ul><li>Credit risk model development using traditional logistic regression and machine learning techniques </li><li>Work closely with collection managers to define models for prioritizing collections efforts.</li><li>Detailed documentation of the model development activity for review from Risk Management </li><li>Challenging the existing procedures to bring in more efficiency to the model development process </li><li>Preparing project presentations for review of Senior Management </li><li>Evaluate various business problems across credit function and proposing model-based solutions </li><li>Mentoring the junior members in the team for day-to-day activities </li><li>Work closely with Cars’24 portfolio teams to understand changes in model performance</li><li>Work on multiple projects and perform other duties and/or special projects as assigned. Provide analytic support on key business initiatives and develop a strong working knowledge of the data warehouse and applicable analytic data systems. Work independently with stakeholders and propose insights for decision making </li></ul> What are we looking for ?<ul><li>Masters /Bachelors Degree in Mathematics/Statistics, Operations Research, Economics, Computer Science/Engineering. </li><li> 8-10 years relevant analytical experience in Scorecard development, ML modelling, Segmentation and Clustering. </li><li>Minimum 2 years- experience in Consumer Credit. </li><li>Must have at least 2 years hands on experience in building credit models using SAS or Python.</li><li>Working knowledge of Logistical/Linear/Regressions CHAID/CART/Clustering techniques.</li><li>Experience working in Hadoop and Bigdata environments. Possess strong coding skills in Python and Pyspark. </li><li>Ability to decipher complex data and effectively present and communicate in a clear and concise manner </li><li>Strong written/oral communication skills and ability to manage multiple projects simultaneously .</li><li>Classical statistical techniques: Regression, Logistic regression, Clustering, Dimensionality reduction techniques, </li><li>Machine Learning algorithms: KNN, NBM, DT, CART, Boosting & Bagging models, SVM, Neural net, Ensemble models etc. </li></ul> Desired Characteristics: <ul><li> Working knowledge of credit bureau/Banking or any alternative data</li><li> Work experience in a financial institution or bank </li><li> Development of Consumer risk models </li><li> Systems Implementation experience.</li></ul>

Job Purpose:A data scientist turns raw data into valuable insights that an organization needs in order to grow and compete. He/she interprets and analyzes data from multiple sources to come up with imaginative solutions to problems. He/she builds AI models and applications which solvereal complex banking business problems. Job Responsibilities:<ul><li>Machine Learning Engineer with strong knowledge of Python and cloud based deployments</li><li>Build, train and deploy models for inferencing and build surrounding APIs to access them on cloud and on-prem.</li><li>You will be part of hands-on team developing ML based applications for the bank using various ML techniques</li><li>You will be required to build and deply ML applications in cloud using NLP, LLMs and other supervised learning techniques.</li><li>You will be required to efficiently understand the data domain of the bank to perform EDA and MI report. And eventually designing and developing ML application on the data for multiple programs.</li><li>Certified in at least one cloud, preferably AWS or GCP.</li></ul>Key Skills:<ul><li>Machine Learning Engineer with strong knowledge of Python and cloud based deployments</li><li>Strong knowledge of EDA, NLP, Topic Modeling, NER, Embedding models and Semantic Search based techniques</li><li>Have working knowledge of LLMs via APIs like Open AI and deploying open source LLMs like LLAMA2 and FLAN T5 etc.</li><li>Strong knowledge of Lang Chain framework and Fast API of python is a must have.</li><li>Knowledge of runtimes like ONNX, Quantization, QLORA techniques</li><li>Working experience of Cloud preferably Azure. Understanding of MLOps frameworks is a big plus.</li></ul>Experience:<ul><li>5- 15 years proven experience as a Data Scientist or Machine Learning Engineer</li></ul>

Data Scientist Jobs in Gurugram

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December 31, 2024

Senior Data Scientist
December 31, 2024

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December 30, 2024

Senior Data Scientist
December 30, 2024

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December 29, 2024

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December 29, 2024

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Data Scientist Jobs in Gurugram

Data ScientistDecember 31, 2024

Senior Data ScientistDecember 31, 2024

Data ScientistDecember 30, 2024

Senior Data ScientistDecember 30, 2024

Data ScientistDecember 29, 2024

Data Scientist Female PreferredDecember 29, 2024