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senior data scientist

AuxoAI

<div>
 
 
 About Auxo AI
 
 
 
 
 Auxo AI is a fast-growing SaS (Service as a Software) company that empowers businesses to harness the power of artificial intelligence for automation, analytics, and smarter decision-making. Our mission is to help organizations accelerate growth by delivering intelligent, scalable, and customer-centric AI solutions leveraging our AI Orchestration platform - Damia.
 
 
 
 
 
 
 
 Role Overview
 
 
 
 
 AuxoAI is hiring a Senior Data Scientist with strong expertise in AI, machine learning engineering (MLE), and generative AI. You will play a leading role in designing, deploying, and scaling production-grade ML systems &mdash; including large language model (LLM)-based pipelines, AI copilots, and agentic workflows. This role is ideal for someone who thrives on balancing cutting-edge research with production rigor and loves mentoring while building impact-first AI applications.&nbsp;
 
 
 
 
 
 
 
 Location
 
 
 :
 
 
 &nbsp;&nbsp;Mumbai/Bengaluru/Hyderabad/ Gurgaon (Hybrid)&nbsp;&ZeroWidthSpace;
 
 
 
 
 
 
 
 Responsibilities
 
 
 :
 
 
 &nbsp;
 
 
 
 
 
 <ul>
 <li>
 
 Own the full ML lifecycle: model design, training, evaluation, deployment&nbsp;
 
 </li>
 <li>
 
 Design production-ready ML pipelines with CI/CD, testing, monitoring, and drift detection&nbsp;
 
 </li>
 <li>
 
 Fine-tune LLMs and implement retrieval-augmented generation (RAG) pipelines&nbsp;
 
 </li>
 <li>
 
 Build agentic workflows for reasoning, planning, and decision-making&nbsp;
 
 </li>
 <li>
 
 Develop both real-time and batch inference systems using Docker, Kubernetes, and Spark&nbsp;
 
 </li>
 <li>
 
 Leverage state-of-the-art architectures: transformers, diffusion models, RLHF, and multimodal pipelines&nbsp;
 
 </li>
 <li>
 
 Collaborate with product and engineering teams to integrate AI models into business applications&nbsp;
 
 </li>
 <li>
 
 Mentor junior team members and promote MLOps, scalable architecture, and responsible AI best practices&nbsp;
 
 </li>
 </ul>
 
 
 
 
 
 Requirements
 
 
 :&nbsp;
 
 
 <ul>
 <li>
 
 5+ years of experience in designing, deploying, and scaling ML/DL systems in production&nbsp;
 
 </li>
 <li>
 
 Proficient in Python and deep learning frameworks such as PyTorch, TensorFlow, or JAX&nbsp;
 
 </li>
 <li>
 
 Experience with LLM fine-tuning, LoRA/QLoRA, vector search (Weaviate/PGVector), and RAG pipelines&nbsp;
 
 </li>
 <li>
 
 Familiarity with agent-based development (e.g., ReAct agents, function-calling, orchestration)&nbsp;
 
 </li>
 <li>
 
 Solid understanding of MLOps: Docker, Kubernetes, Spark, model registries, and deployment workflows&nbsp;
 
 </li>
 <li>
 
 Strong software engineering background with experience in testing, version control, and APIs&nbsp;
 
 </li>
 <li>
 
 Proven ability to balance innovation with scalable deployment&nbsp;
 
 </li>
 <li>
 
 B.S./M.S./Ph.D. in Computer Science, Data Science, or a related field&nbsp;
 
 </li>
 <li>
 
 Bonus: Open-source contributions, GenAI research, or applied systems at scale&nbsp;
 
 </li>
 </ul>
 
 
 
 
 
 Why Join AuxoAI?
 
 
 <ul>
 <li>
 
 Be part of a mission-driven company transforming how businesses use AI.
 
 </li>
 <li>
 
 Opportunity to shape marketing from the ground up at a fast-scaling SaS company.
 
 </li>
 <li>
 
 Collaborative, innovative, and growth-oriented culture.
 
 </li>
 <li>
 
 Competitive compensation, benefits, and equity.
 
 </li>
 </ul>
 
 
 
</div>

Senior Data Scientist - AI/ML

UsefulBI Corporation

<div>
 
 Job Title: Gen AI Developer
 
 
 Location: Bangalore / Lucknow
 
 
 Role Type: Full-time, Senior level
 
 
 Company&rsquo;s website: https://usefulbi.com
 
 
 LinkedIn link: UBI LinkedIn
 
 
 
 
 
 About UsefulBI:
 
 
 UsefulBI is a leading AI-driven data solutions provider specialising in data engineering, cloud transformations, and AI-powered analytics for Fortune 500 companies. We help businesses turn complex data into actionable insights through our innovative products and services.
 
 
 
 
 
 Role Overview:
 
 
 We are seeking a Senior Data Scientist / Gen AI Developer who is passionate about transforming raw data into intelligent business insights and building AI models that solve real-world problems. In this role, you&rsquo;ll work across the entire data science lifecycle&mdash;from exploratory analysis and statistical modeling to deploying advanced LLM-based and Generative AI solutions.
 
 
 
 
 
 You will be at the forefront of building AI-powered products across domains like healthcare, life sciences, finance, and enterprise analytics, with a focus on real-world impact and scalable architecture.
 
 
 
 
 
 Key Responsibilities:
 
 
 &bull; Develop and deploy applications using Large Language Models (LLMs) like GPT-4, Claude, LLaMA, and Gemini.
 
 
 &bull; Build GenAI-powered tools such as AI report generators, contextual chatbots, summarization engines, and semantic search applications.
 
 
 &bull; Design, optimize, and evaluate prompts tailored for various use cases and user personas.
 
 
 &bull; Implement and enhance Retrieval-Augmented Generation (RAG) workflows for improved relevance and accuracy.
 
 
 &bull; Fine-tune and customize foundation models using techniques like LoRA, PEFT, and prompt-tuning.
 
 
 &bull; Evaluate and monitor model performance on accuracy, latency, and business-specific KPIs.
 
 
 &bull; Apply NLP techniques such as entity recognition, topic modeling, summarization, sentiment analysis, and question answering.
 
 
 &bull; Work with libraries and frameworks such as Hugging Face Transformers, Lang Chain, spaCy, and NLTK.
 
 
 &bull; Deploy GenAI applications using cloud platforms like AWS Bedrock/SageMaker, GCP Vertex AI, or Azure OpenAI.
 
 
 &bull; Build scalable and secure inference pipelines integrated with backend systems and APIs.
 
 
 &bull; Use tools like MLflow and Docker for model lifecycle management and MLOps best practices.
 
 
 &bull; Collaborate with cross-functional teams including product managers, data engineers, and designers to align AI outputs with business needs.
 
 
 &bull; Continuously experiment with new GenAI models, tools, and research to keep the solutions cutting-edge.
 
 
 
 
 
 Required Skills and Qualifications:
 
 
 &bull; 7+ years of experience as a Data Scientist with good experience in Generative AI or LLM-based applications.
 
 
 &bull; Strong expertise in Python and libraries like Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch.
 
 
 &bull; Experience in end-to-end ML lifecycle including model development, validation, and deployment. &bull; Solid understanding of statistics, probability, and data modeling.
 
 
 &bull; Experience with NLP libraries (NLTK, spaCy, Hugging Face Transformers).
 
 
 &bull; Hands-on experience with GenAI tools: OpenAI APIs, LangChain, RAG, LLM fine-tuning.
 
 
 &bull; Experience with SQL and at least one NoSQL database.
 
 
 &bull; Familiarity with cloud platforms (AWS, GCP, Azure) and version control (Git).
 
 
 &bull; Strong communication skills with the ability to explain complex models to non-technical audiences.
 
 
 
</div>

Data Scientist(Gen AI , Databricks)

<div>
 At EY, you&rsquo;ll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture and technology to become the best version of you. And we&rsquo;re counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all.
 
 
 
 EY GDS &ndash; Data and Analytics (D&amp;A) &ndash; Senior &ndash; Senior Data Scientist
 
 
 
 Role Overview: We are seeking a highly skilled and experienced Senior Data Scientist with a minimum of 3 - 7 years of experience in Data Science and Machine Learning, preferably with experience in NLP, Generative AI, LLMs, MLOps, Optimization techniques, and AI solution Architecture. In this role, you will play a key role in the development and implementation of AI solutions, leveraging your technical expertise. The ideal candidate should have a deep understanding of AI technologies and experience in designing and implementing cutting-edge AI models and systems. Additionally, expertise in data engineering, DevOps, and MLOps practices will be valuable in this role.
 
 
 
 Responsibilities:
 
 
 
 
 Your technical responsibilities:
 
 
 
 <ul>
 <li>
 Contribute to the design and implementation of state-of-the-art AI solutions.
 </li>
 <li>
 Assist in the development and implementation of AI models and systems, leveraging techniques such as Language Models (LLMs) and generative AI.
 </li>
 <li>
 Collaborate with stakeholders to identify business opportunities and define AI project goals.
 </li>
 <li>
 Stay updated with the latest advancements in generative AI techniques, such as LLMs, and evaluate their potential applications in solving enterprise challenges.
 </li>
 <li>
 Utilize generative AI techniques, such as LLMs, to develop innovative solutions for enterprise industry use cases.
 </li>
 <li>
 Integrate with relevant APIs and libraries, such as Azure Open AI GPT models and Hugging Face Transformers, to leverage pre-trained models and enhance generative AI capabilities.
 </li>
 <li>
 Implement and optimize end-to-end pipelines for generative AI projects, ensuring seamless data processing and model deployment.
 </li>
 <li>
 Utilize vector databases, such as Redis, and NoSQL databases to efficiently handle large-scale generative AI datasets and outputs.
 </li>
 <li>
 Implement similarity search algorithms and techniques to enable efficient and accurate retrieval of relevant information from generative AI outputs.
 </li>
 <li>
 Collaborate with domain experts, stakeholders, and clients to understand specific business requirements and tailor generative AI solutions accordingly.
 </li>
 <li>
 Conduct research and evaluation of advanced AI techniques, including transfer learning, domain adaptation, and model compression, to enhance performance and efficiency.
 </li>
 <li>
 Establish evaluation metrics and methodologies to assess the quality, coherence, and relevance of generative AI outputs for enterprise industry use cases.
 </li>
 <li>
 Ensure compliance with data privacy, security, and ethical considerations in AI applications.
 </li>
 <li>
 Leverage data engineering skills to curate, clean, and preprocess large-scale datasets for generative AI applications.
 
 
 </li>
 </ul>
 
 Requirements:
 
 
 
 <ul>
 <li>
 Bachelor's or Master's degree in Computer Science, Engineering, or a related field. A Ph.D. is a plus.
 </li>
 <li>
 Minimum 3-7 years of experience in Data Science and Machine Learning.
 </li>
 <li>
 In-depth knowledge of machine learning, deep learning, and generative AI techniques.
 </li>
 <li>
 Proficiency in programming languages such as Python, R, and frameworks like TensorFlow or PyTorch.
 </li>
 <li>
 Strong understanding of NLP techniques and frameworks such as BERT, GPT, or Transformer models.
 </li>
 <li>
 Familiarity with computer vision techniques for image recognition, object detection, or image generation.
 </li>
 <li>
 Experience with cloud platforms such as Azure, AWS, or GCP and deploying AI solutions in a cloud environment.
 </li>
 <li>
 Expertise in data engineering, including data curation, cleaning, and preprocessing.
 </li>
 <li>
 Knowledge of trusted AI practices, ensuring fairness, transparency, and accountability in AI models and systems.
 </li>
 <li>
 Strong collaboration with software engineering and operations teams to ensure seamless integration and deployment of AI models.
 </li>
 <li>
 Excellent problem-solving and analytical skills, with the ability to translate business requirements into technical solutions.
 </li>
 <li>
 Strong communication and interpersonal skills, with the ability to collaborate effectively with stakeholders at various levels.
 </li>
 <li>
 Understanding of data privacy, security, and ethical considerations in AI applications.
 </li>
 <li>
 Track record of driving innovation and staying updated with the latest AI research and advancements.
 
 
 </li>
 </ul>
 
 Good to Have Skills:
 
 
 
 <ul>
 <li>
 Apply trusted AI practices to ensure fairness, transparency, and accountability in AI models and systems.
 </li>
 <li>
 Utilize optimization tools and techniques, including MIP (Mixed Integer Programming).
 </li>
 <li>
 Drive DevOps and MLOps practices, covering continuous integration, deployment, and monitoring of AI models.
 </li>
 <li>
 Implement CI/CD pipelines for streamlined model deployment and scaling processes.
 </li>
 <li>
 Utilize tools such as Docker, Kubernetes, and Git to build and manage AI pipelines.
 </li>
 <li>
 Apply infrastructure as code (IaC) principles, employing tools like Terraform or CloudFormation.
 </li>
 <li>
 Implement monitoring and logging tools to ensure AI model performance and reliability.
 </li>
 <li>
 Collaborate seamlessly with software engineering and operations teams for efficient AI model integration and deployment.
 </li>
 <li>
 Familiarity with DevOps and MLOps practices, including continuous integration, deployment, and monitoring of AI models.
 
 
 </li>
 </ul>
 
 EY | Building a better working world
 
 
 
 EY exists to build a better working world, helping to create long-term value for clients, people and society and build trust in the capital markets.
 
 
 Enabled by data and technology, diverse EY teams in over 150 countries provide trust through assurance and help clients grow, transform and operate.
 
 
 Working across assurance, consulting, law, strategy, tax and transactions, EY teams ask better questions to find new answers for the complex issues facing our world today.
</div>

EY - GDS Consulting - AI And DATA -Gen AI - Senior

Valiance Solutions

<div>
 
 
 About Us:
 
 
 
 At Valiance, we empower businesses with AI-driven insights and data analytics solutions. Specializing in demand forecasting within retail Industry very specific to
 
 Apparel and Footwear
 
 domains, we leverage standardized ML models to deliver accurate forecasting outcomes to our clients. We are looking for a skilled Data Scientist who can interpret and improve these models to drive real-world business results.
 
 
 
 
 
 
 Role Overview:
 
 
 
 The Data Scientist will be responsible for applying our pre-trained demand forecasting models to generate actionable insights and highly accurate forecasting outcomes. This role involves thorough data analysis, identifying trends and anomalies, interpreting results, and communicating findings effectively to a non-technical business audience. The ideal candidate is less focused on creating algorithms and more oriented towards solving business challenges and providing insights that make a tangible impact.
 
 
 
 
 
 
 Key Responsibilities:
 
 
 <ul>
 <li>
 
 Data Analysis:
 
 Conduct in-depth data analysis to identify trends, patterns, and anomalies in demand/Timeseries forecasting for Retail Industry very specific to Apparel and Footwear (must have)
 </li>
 <li>
 
 Model Utilization:
 
 Leverage existing pre-trained forecasting models, optimizing their performance by incorporating a nuanced understanding of data points and improving model outcomes based on data insights.
 </li>
 <li>
 
 Interpretation &amp; Communication:
 
 Interpret model results and explain outcomes in simple, actionable terms for business stakeholders, ensuring clarity and relevance.
 </li>
 <li>
 
 Insights Generation:
 
 Develop insights that guide business decisions, aiming for highly accurate forecasting outcomes to meet business requirements.
 </li>
 <li>
 
 Collaboration:
 
 Work closely with cross-functional teams, including business stakeholders and analysts, to ensure forecasting outputs align with business objectives and provide real-world value.
 </li>
 <li>
 
 Continuous Improvement:
 
 Identify opportunities to improve model performance through better data usage and fine-tuning, rather than new model development.
 </li>
 </ul>
 
 
 
 
 
 Required Skills &amp; Qualifications:
 
 
 <ul>
 <li>
 
 Experience:
 
 
 3-6 years of experience
 
 in data science or a related field, specifically in
 
 Demand/Timeseries forecasting for Retail Industry very specific to Apparel and Footwear (must have)
 
 </li>
 <li>
 
 Technical Proficiency:
 
 Strong skills in data analysis, data visualization, and working with pre-trained ML models. Proficiency in Python, and SQL is preferred.
 </li>
 <li>
 
 Business Focus:
 
 Strong orientation towards solving business problems rather than a pure focus on machine learning algorithms.
 </li>
 <li>
 
 Communication Skills:
 
 Ability to clearly communicate insights and forecast results to non-technical stakeholders in simple, understandable language.
 </li>
 <li>
 
 Problem Solving:
 
 Demonstrated ability to interpret data, uncover actionable insights, and suggest practical solutions for business needs.
 </li>
 <li>
 
 Detail-Oriented:
 
 Thorough attention to detail, ensuring accuracy in forecasting and relevance of insights.
 </li>
 <li>
 
 Educational Background:
 
 Bachelor&rsquo;s or Master&rsquo;s degree in Data Science, Statistics, Computer Science, or a related field.
 </li>
 </ul>
 
 
</div>

Data Scientist

AB InBev GCC India

<div>
 
 AB InBev GCC was incorporated in 2014 as a strategic partner for Anheuser-Busch InBev. The center leverages the power of data and analytics to drive growth for critical business functions such as operations, finance, people, and technology. The teams are transforming Operations through Tech and Analytics.
 
 
 
 
 
 Do You Dream Big?
 
 
 
 
 
 We Need You.
 
 
 
 
 
 
 Job Title: Data Scientist
 
 
 
 
 
 
 
 Location: Bangalore
 
 
 
 
 
 
 
 Reporting to: Manager- Analytics/ Senior Manager-Analytics
 
 
 
 
 
 
 
 1. PURPOSE OF THE ROLE
 
 
 
 
 
 
 Contributing to the Data Science efforts of AB InBevʼs global non-commercial analytics capability of Supply Analytics. Candidate will be required to contribute and
 
 
 may also need to guide the DS team staffed on the area and assess the efforts required to scale and standardize the use of Data Science across multiple ABI markets
 
 
 
 
 
 
 2. KEY TASKS AND ACCOUNTABILITIES
 
 
 
 
 
 <ul>
 <li>
 Understand the business problem and translate that to an analytical problem; participate in the solution design process.
 </li>
 <li>
 Manage the full AI/ML lifecycle, including data preprocessing, feature engineering, model training, validation, deployment, and monitoring.
 </li>
 <li>
 Develop reusable and modular Python code adhering to OOP (Object-Oriented Programming) principles.
 </li>
 <li>
 Design, develop, and deploy machine learning models into production environments on Azure.
 </li>
 <li>
 Collaborate with data scientists, software engineers, and other stakeholders to meet business needs.
 </li>
 <li>
 Ability to communicate findings clearly to both technical and business stakeholders.
 </li>
 </ul>
 
 
 
 
 
 3. Qualifications, Experience, Skills
 
 
 
 
 
 
 
 Level of educational attainment required (1 or more of the following)
 
 
 <ul>
 <li>
 B. Tech /BE/ Masters in CS/IS/AI/ML.
 </li>
 </ul>
 
 
 
 
 
 Previous work experience required
 
 
 <ul>
 <li>
 Minimum 3 years of relevant experience.
 </li>
 </ul>
 
 
 
 
 
 Technical skills required
 
 
 
 
 
 
 
 Must Have
 
 
 <ul>
 <li>
 Strong expertise in Python, SQL, and libraries such as Scikitlearn, Pandas, NumPy, and PyTorch or TensorFlow including advanced knowledge of OOP concepts.
 </li>
 <li>
 Exposure to AI/ML methodologies with a previous hands-on experience in ML concepts like forecasting, clustering, regression, classification, optimization using Python.
 </li>
 <li>
 Azure Tech Stack, Databricks, ML Flow in any cloud platform Airflow for orchestrating and automating workflows.
 </li>
 <li>
 Strong knowledge of feature engineering, model training, and validation techniques.
 </li>
 <li>
 MLOPS concepts and containerization tools like Docker.
 </li>
 <li>
 Experience with version control tools such as Git.
 </li>
 <li>
 Consistently display an intent for problem solving. Strong communication skills (vocal and written).
 </li>
 <li>
 Ability to effectively communicate and present information at various levels of an organization.
 </li>
 <li>
 Experience in model evaluation, A/B testing, and back testing methodologies.
 </li>
 </ul>
 
 
 
 
 
 Good To Have
 
 
 <ul>
 <li>
 Preferred industry exposure in Manufacturing Domain.
 </li>
 <li>
 Product building experience.
 </li>
 </ul>
 
 
 
 
 
 Other Skills required
 
 
 <ul>
 <li>
 Passion for solving problems using data.
 </li>
 <li>
 Detail oriented, analytical and inquisitive.
 </li>
 <li>
 Ability to learn on the go.
 </li>
 <li>
 Ability to work independently and with others.
 </li>
 </ul>
 
 
 
 
 We dream big to create future with more cheers!
 
</div>

Equifax

<div>
 
 Synopsis of the role
 
 
 
 Join our Identity and Fraud Solution Analytics group as a Data Scientist, where you will play a pivotal role Analyze
 
 
 multiple complex data sources using statistical analysis and programming languages to inform business decision
 
 
 making. Delivers analytical and commercial solutions for internal and external customers. Develops models and
 
 
 other analyses to test hypotheses and understand the potential impacts of decisions under various scenarios. Able
 
 
 to communicate analytical results to generate improved business decisions and profitability. Combines business
 
 
 requirements and existing processes and data knowledge to create analytical solutions.
 
 
 
 What You&rsquo;ll Do
 
 
 
 <ul>
 <li>
 Utilize combined knowledge of data structures, analytics, algorithms/models, and strong computer science
 
 
 </li>
 </ul>
 fundamentals to prepare datasets, conduct analytics, and develop deployable solutions with guidance from
 
 
 more senior resources.
 
 
 <ul>
 <li>
 Leverage knowledge of data structures and algorithms to analyze and prepare data for analysis, assembling
 
 
 </li>
 </ul>
 data from standard and new data sources
 
 
 <ul>
 <li>
 Able to analyze and prepare complex and new data sources and incorporate them into analytical solutions
 </li>
 <li>
 Collaborate with stakeholders to improve model performance, interpret results, and provide actionable
 
 
 </li>
 </ul>
 insights.
 
 
 <ul>
 <li>
 Works on moderate complexity tasks in problems often within multiple business or analytical domains,
 
 
 </li>
 </ul>
 collaborating with other teams to develop predictive models, risk assessments, fraud detection,
 
 
 recommendation engines, etc.
 
 
 <ul>
 <li>
 Package, summarize and visualize analytical findings and results for management.
 </li>
 <li>
 Evaluate the work of peer and/or junior data scientists to ensure high quality solutions
 </li>
 <li>
 Prioritizes and organizes own work to meet deadlines and deliver quality results
 </li>
 <li>
 Identifies and solves a range of problems in straightforward situations.
 </li>
 <li>
 Design, management and delivery of analytical insights and solutions through data analysis, data
 
 
 </li>
 </ul>
 management and data science.
 
 
 <ul>
 <li>
 Primary activities include delivering technical, business strategic expertise and ensuring proper governance
 
 
 </li>
 </ul>
 of data sources, models, attributes and analytic platforms. Accountable for the data and insight strategy and
 
 
 its execution for the company
 
 
 
 What Experience You Need
 
 
 
 <ul>
 <li>
 BS degree in a STEM major or equivalent discipline.
 </li>
 <li>
 2-5 years of experience in a related analytical role, including experience with the design and development of
 
 
 </li>
 </ul>
 predictive models
 
 
 <ul>
 <li>
 Requires knowledge and experience in own discipline; still acquiring higher-level knowledge and skills
 </li>
 <li>
 Python/SQL coding experience is a must have technical skill.
 </li>
 <li>
 Artificial Intelligence - Utilize artificial intelligence to improve process efficiency, effectiveness and products
 </li>
 <li>
 Collaboration - Work collaboratively across different projects, communicating technical details to technical
 
 
 </li>
 </ul>
 and non-technical stakeholders. Manage own priorities within and across teams.
 
 
 <ul>
 <li>
 Commercial Acumen - Have a good understanding of a product and related market segments and
 
 
 </li>
 </ul>
 understand the technical intricacies of how this product solves a commercial problem.
 
 
 <ul>
 <li>
 Decision Modeling - Understand advanced statistical concepts used to contribute to the development of
 
 
 </li>
 </ul>
 stress tested deployable machine learning algorithms (Logistic Regression, Xgboost, Neural Networks, etc.).
 
 
 <ul>
 <li>
 Leadership and Teamwork - Participate in a collaborative and productive team environment and take charge
 
 
 </li>
 </ul>
 of technical and self development
 
 
 <ul>
 <li>
 Problem Solving - Utilize hypothesis based problem solving to deliver pragmatic resolutions to business
 
 
 </li>
 </ul>
 problems.
 
 
 <ul>
 <li>
 Statistical Programming - Execute and contribute to version controlled code and make use-case-specific
 
 
 </li>
 </ul>
 modifications as needed. Manipulate and work with unstructured/structured, small and big data
 
 
 
 What Could Set You Apart
 
 
 
 <ul>
 <li>
 Cloud certification strongly preferred.
 </li>
 <li>
 Additional role-based certifications may be required depending upon region/BU requirements.
 </li>
 <li>
 lending, credit risk and marketing analytics space - both in India &amp; International.
 </li>
 <li>
 Chance to use cutting-edge statistical/modeling tools across literally hundreds of data assets.
 </li>
 <li>
 Offices located in the center of Bangalore &amp; Mumbai.
 </li>
 <li>
 Utilize artificial intelligence to improve process efficiency, effectiveness and products
 </li>
 <li>
 Equifax D&amp;A University: skill lab, group &amp; individual learning.
 </li>
 </ul>
</div>

Data Scientist, Product Analytics

Explore 317+ Senior data scientist in Mangaluru this November. Find roles across top companies and apply now to boost your career.

317 senior data scientist jobs IN Mangaluru

Senior Data Scientist - AI/ML

Data Scientist(Gen AI , Databricks)

EY - GDS Consulting - AI And DATA -Gen AI - Senior

Data Scientist

Data Scientist

Data Scientist

Data Scientist, Product Analytics