131 Data Scientist Jobs - Page 2

Role Synopsis This role is a senior-level position within a data science team, responsible for providing leadership, strategic direction, and technical expertise in the field of data science and machine learning. This role involves leading all aspects of and guiding a team of data scientists while collaborating closely with multi functional departments, such as engineering, product management, and business collaborators. The Lead Data Scientist plays a pivotal role in crafting data-driven strategies and solutions that chip in to the organization's success and growth Key Accountabilities Data Analysis and Modeling: Lead data scientists must have a confirmed foundation in data analysis and a deep understanding of various machine learning algorithms They should be able to apply these techniques to address sophisticated problems and extract valuable insights from data Out of Code computing: Use libraries that support out-of-core computing, such as Dask in Python These libraries can process data that doesn't fit into memory by reading it in smaller portions from disk Business Insight: Understanding the FDO's business objectives and aligning data initiatives with them Project Management: Being skilled in project management methodologies helps in planning and driving data science projects efficiently Machine Learning: Innovation and Strategy - Advanced Machine Learning Skills for complex models. Evaluation Collaboration and Communication: Effective communication with collaborators, Explain the modeling approach and results. Implement to privacy guidelines and recommendation with conscious balance Continuous Learning: Staying up-to-date in competitive edge. Apply methodologies to practical business challenges. Meeting with domain GPO's Data cleaning and preprocessing, analysis: The ability to clean and preprocess data effectively is a fundamental skill in any data science role Data Ethics and Privacy: Open communication with customer. Ethical considerations in algorithm design. Secure data handling, Data minimization Database Management: Proficient in database systems and SQL is required for data retrieval and storage Domain knowledge: Expertise in the domain they are working in to understand the context and requirements of the data projects better Statistical Analysis and Mathematics: Solid grasp of statistical methods and mathematical concepts is needed for data analysis, modeling, and drawing substantial insights from data Experience and Job Requirements Data Science Team plays a crucial role in driving data-informed decision-making and generating actionable insights to support the company's goals. This team is responsible for processing, analyzing, and interpreting large and complex datasets from multiple datasets to provide valuable insights and recommendations across various domains. Through advanced analytical techniques and machine learning models, the data science team helps optimize processes, predict trends, and build data-driven strategies. A bachelor's or equivalent experience or master's degree in quantitative, qualitative field such as Computer Science, Statistics, Mathematics, Physics, Engineering, or a related data field is often required Skills: Leadership role in Data Analysis, Programming proficiency in Python, SQL, Azure Databricks, Statistics & Mathematics. Leadership qualities to steer the team. Strategic direction and technical expertise Soft skills: Active listening, Translate business problems into data questions, Communication and collaboration, Presentation, Problem solving, Multi-functional, Team management, Partner management Data Sources: SAP, Concur, Salesforce, Workday, Excel files Other: Project management. Domain knowledge [Procurement, Finance, Customer], Business Insight, Critical thinking, Story telling Able to prepare analytical reports, presentations and/or visualisation dashboards to communicate findings, important metrics and insights to both technical and non-technical customers Stay up to date with industry trends, standard methodologies and new technologies in data analytics, machine learning, data science techniques.

Title: ML Engineer Location: Chennai (Hybrid) Experience: 3 - 12 Years Notice Period: 15-20 Days Responsibilities: Strong understanding of ML algorithms, techniques, and best practices. Strong understanding of Databricks, Azure AI services and other ML platforms and cloud computing platforms (e.g., AWS, Azure, GCP) and frameworks (e.g., TensorFlow, PyTorch, scikit-learn). Strong understanding of Mlflow or Kubeflow frameworks Strong programming skills in python and Data analytical expertise Experience in building Gen AI based solutions like chatbots using RAG approaches Expertise in any of the gen ai frameworks such as Lang chain/ Lang graph, autogen, crewai, etc. Requirements: Proven experience as a Machine Learning Engineer, Data Scientist, or similar role, with a focus on product matching, image matching, and LLM. Solid understanding of machine learning algorithms and frameworks (e.g., TensorFlow, PyTorch, Scikit-learn). Hands-on experience with product matching algorithms and image recognition techniques. Experience with natural language processing and large language models (LLMs) such as GPT, BERT, or similar architectures. Optimize and fine-tune models for performance and scalability.. Collaborate with cross-functional teams to integrate ML solutions into products. Stay updated with the latest advancements in AI and machine learning.

Warm Greetings from SP Staffing!! Role :Data Scientist Experience Required :5 to 10 yrs Work Location :Hyderabad/Bangalore/Chennai Required Skills, Python GCP AI Platform, BigQuery ML, Cloud AutoML, and Vertex AI. Interested candidates can send resumes to nandhini.spstaffing@gmail.com

Experience using Python, SciKit, SQL, Snowflake, hit-level Adobe Analytics data, product usage data, Jupyter Notebooks, Amazon SageMaker, Airflow, Github. Proficiency with data mining, mathematics, and statistical analysis techniques. Required Candidate profile 5+ yrs experience as Data Scientist Strong knowledge with Deep Learning & Machine Learning,LLM knowledge & experience with SQL & python is must Must be from Ahmadabad or open to relocate to Ahmadabad

Key Responsibilities: AI-Driven Development: Design and develop an intelligent data conversion application using AI technologies. Data Mapping & Validation: Implement AI algorithms to accurately map source-to-target data and validate integrity. Automated Code Generation: Develop AI models to automate code creation for transformation scripts. Code Conversion: Use AI to facilitate smooth and efficient legacy-to-modern code conversion. Monitoring & Troubleshooting: Ensure the health and performance of the AI-powered conversion system. Cross-Functional Collaboration: Work closely with data engineers, developers, AI/ML engineers, and business analysts. Documentation: Maintain detailed records of models, processes, and tools used. Continuous Learning: Stay abreast of the latest trends in AI, ML, data science, and cloud technologies. What Youll Need: Bachelor's or Master’s in Data Science , Computer Science , Artificial Intelligence , or a related field. Strong experience in Python , SQL , and other relevant programming languages. Hands-on with AI/ML frameworks like TensorFlow, PyTorch, etc. Proven experience with AI-driven data mapping , code generation , and validation techniques . Knowledge of code conversion methodologies and tools. Experience working with databases such as SQL Server and MongoDB . Strong analytical and problem-solving abilities. Excellent collaboration and communication skills. High attention to detail and data accuracy. Comfortable with a "fail fast, learn faster" approach in agile, fast-paced environments. 5+ years of relevant industry experience. Preferred Qualifications: Experience in the Financial Services domain with awareness of compliance requirements. Certifications in Data Science or AI/ML. Familiarity with data wrangling , ETL processes , and Master Data Management . Exposure to DevOps tools like Jira, Bitbucket, and Confluence. Hands-on with Azure technologies : Cognitive Services, Synapse Analytics, Databricks, and Azure ML. Prior experience delivering AI-powered data solutions , such as: Seamless Data Schema Conversion AI-Driven Data Validation for Migration Intelligent Code Generation Historical Data Transformation and Archiving AI-Augmented Reconciliation and Error Detection

Should have exp with Agen c frameworks like Crew AI, Lang, graph, Swarm AI etc. Must have contributed significantly to the development of at least 2 Gen AI projects. Must have worked with mul ple Gen AI models including GPT, Claude, Qwen, Lama etc.

Data Scientist Mumbai One of the leading Bank mail at manjeet.kaur@mounttalent.com Whatsapp at 8384077438 Roles and Responsibilities Qualifications • 2-4 years experience in Analytics and Machine Learning & Deep learning(Sentiment Analysis, Text Mining, Entity Extraction, Document Classification, Topic Modeling, Natural Language Understanding (NLU) and Natural Language Generation (NLG)). • Good Experience in Web Scraping or data extraction through Selenium/Scrapy or other frameworks and related libraries (like beautifulsoup). • Knowldge of advanced scraping techniques (like overcoming captcha, proxy, browser fingerprinting, bot detection bypassing,etc) • Working knowledge in various DBs(MySQL, HBase, MongoDB), message queues & Web RestFul APIs. • Expertise in open-source NLP toolkits such as CoreNLP, OpenNLP, NLTK, gensim, LingPipe, Keras, Tensorflow, Mallet, ML/math toolkits such as scikit-learn, MLlib, Theano, NumPyetc. • Experience of Testing & deployment of Machine learning/deep learning projects in the desired platform. • Strong Logical & Analytical skills with good soft & communication skills Industry Preferably from a Technology, ITES, Shared Services or Banking organization Key Responsibilities • Build, Improve and extend NLP capabilities • Select the proper annotated datasets for supervised learning techniques • Use effective text representation techniques to develop useful features • Identify and utilize the correct algorithms for specific NLP projects • Develop NLP projects in accordance with prescribed requirements • Train developed NLP models and evaluated their effectiveness • Conduct statistical analyses of models, and adjust models where possible • Extend machine learning frameworks and libraries for NLP projects Certifications Certification in Google Tensor Flow, Hadoop, Python, PySpark, SQL, R is desirable Employment Type All positions are on fixed term contract on a full-time basis exclusively for ReBIT, initially for a period of five years, extendable by mutual consent Location Navi Mumba

Job Title: Principal Machine Learning Architect Location: Bengaluru, Hybrid Department: Engineering / Data Science Reports To: Head of AI/ML About the Role: We are seeking a highly experienced Principal Machine Learning Architect to lead the design, development, and deployment of large-scale, high-impact ML solutions across our organization. As a thought leader, you will drive the ML roadmap, architect end-to-end solutions, and ensure our ML infrastructure is scalable, secure, and production-ready. Key Responsibilities: Architecture Leadership: Design and oversee the implementation of scalable, reliable, and efficient machine learning architectures. End-to-End Ownership: Lead the entire ML lifecycle from problem definition, data ingestion, feature engineering, model development, deployment, and monitoring. Strategic Guidance: Define best practices for ML system design, governance, LLM, NLP, Deep Learning, Machine Learning, RAG, MLOps, and responsible AI practices. Collaboration: Work cross-functionally with data scientists, ML engineers, product managers, and infrastructure teams to ensure alignment and integration. Innovation: Evaluate and incorporate new tools, techniques, and research to improve model performance and infrastructure. Mentorship: Provide technical mentorship to ML engineers and data scientists; promote a culture of technical excellence and continuous learning. Scalability: Architect and optimize ML solutions for scalability, performance, and maintainability in cloud and hybrid environments. Security & Compliance: Ensure models and data pipelines adhere to security, fairness, and compliance standards. Required Qualifications: 10+ years of experience in software engineering or data science with at least 5 years in ML architecture or applied ML roles. Advanced degree (MS/PhD) in Computer Science, Machine Learning, Data Science, or a related field. Proven experience building and deploying ML systems at scale (e.g., recommendation systems, NLP, computer vision, time series). Strong proficiency in Python and ML frameworks (e.g., TensorFlow, PyTorch, scikit-learn). Deep understanding of data infrastructure, distributed computing, and modern MLOps practices (e.g., MLflow, Kubeflow, Airflow). Familiarity with cloud platforms (AWS, GCP, Azure) and container technologies (Docker, Kubernetes). Strong knowledge of data privacy, model governance, and responsible AI principles. Preferred Qualifications: Experience with generative AI or LLM deployment. Contributions to open-source ML projects or research publications. Familiarity with data mesh, feature stores, or real-time ML pipelines. Strong communication and leadership skills.Role & responsibilities Preferred candidate profile

We are seeking a skilled and innovative AI/ML Engineer to design, develop, and implement machine learning models and artificial intelligence solutions that drive business impact. The ideal candidate will have strong experience in data science, statistical modeling, and deep learning frameworks, along with the ability to work in cross-functional teams. Build and deploy scalable ML models for classification, regression, recommendation, or NLP tasks. Collect, clean, and preprocess large datasets from various sources. Design and run experiments to evaluate model performance and improve accuracy. Collaborate with software engineers to integrate models into production systems. Stay updated with the latest AI/ML research and technologies to apply best practices. Optimize model performance and ensure alignment with business goals.

data scientist engineer,AI/ML,Data collection,Architecture creation,Python,R,Data analysis,Panda, Numpy and Matplot Lib,Git,Tensorflow,Pytorch, Scikit-Learn, Keras,Cloud platform( AWS/ AZure/ GCP), Docker kubernetis, Big Data,Hadoop, Spark,

The Senior Data Scientist's primary responsibility is to lead the delivery of multiple analytics projects and tools within the Retail domain, ensuring high-quality analytical solutions while managing and mentoring junior team members. This role requires collaborating with stakeholders across multiple teams to transform complex business questions into actionable analytical solutions while maintaining technical excellence and commercial impact. How will you make an impact? Technical Leadership: Lead the analytics quality and delivery of key projects, ensuring alignment on outputs and timelines with stakeholders Data Analytics: Perform sophisticated data exploration and develop efficient code for complex data transformations Solution Design: Transform client questions into analytical solutions through project scoping and solution design Commercial Translation: Connect analytical outputs to business outcomes and communicate insights to both technical and non-technical audiences Team Development: Mentor junior team members and actively participate in knowledge sharing initiatives Process Excellence: Identify and implement improvements in analytical workflows and coding practices The superpowers youll be bringing to the team: Analytics Mastery: Over 4 years of experience in a highly technical analytics environment, with strong coding skills in SQL, Python, and Snowflake, and expertise in handling large datasets to solve commercial business problems. Commercial Insight: Strong commercial acumen to understand business needs and suggest impactful analytics solutions, with experience in transforming client questions into actionable insights. Leadership Excellence: Proven experience in supervising and leading teams as a senior team member, project manager, or team leader, with a strong track record of managing internal and external stakeholders in dynamic, deadline-driven environments. People Development: Passionate about people management, mentoring, and development, with a keen interest in fostering team growth and success. Educational Foundation: Strong academic background with tertiary qualifications in engineering, mathematics, actuarial studies, statistics, physics, or a related discipline.

We are looking for a highly skilled and analytical Data Scientist to join our team. You will be responsible for analyzing large datasets to extract actionable insights, build predictive models, and support data-driven decision-making across the organization. The ideal candidate should be passionate about data, statistical analysis, and applying machine learning techniques to solve real-world business problems. Key Responsibilities: Collect, clean, and preprocess large datasets from multiple sources. Analyze complex data sets to identify patterns, trends, and opportunities. Design and implement machine learning models to solve business challenges. Communicate findings through data visualizations, dashboards, and reports. Collaborate with cross-functional teams (engineering, product, marketing) to implement data solutions. Monitor and maintain model performance and retrain when necessary. Stay updated on the latest developments in AI/ML and data science tools. Required Skills and Qualifications: Bachelors / Masters/Ph.D. in Computer Science, Statistics, Mathematics, Data Science, or a related field. Strong proficiency in Python or R, along with libraries such as Pandas, NumPy, Scikit-learn, TensorFlow, or PyTorch. Experience with data querying languages such as SQL. Good understanding of statistical analysis, machine learning, and data mining techniques. Locations : Mumbai, Delhi / NCR, Bengaluru , Kolkata, Chennai, Hyderabad, Ahmedabad, Pune, Remote

Role Summary : We are seeking a highly skilled Senior Data Science Consultant with 8+ years of experience to lead an internal optimization initiative. The ideal candidate should have a strong background in data science, operations research, and mathematical optimization, with a proven track record of applying these skills to solve complex business problems. This role requires a blend of technical depth, business acumen, and collaborative communication. A background in internal efficiency/operations improvement or cost/resource optimization projects is highly desirable. Key Responsibilities : - Lead and contribute to internal optimization-focused data science projects from design to deployment. - Develop and implement mathematical models to optimize resource allocation, process performance, and decision-making. - Use techniques such as linear programming, mixed-integer programming, heuristic and metaheuristic algorithms. - Collaborate with business stakeholders to gather requirements and translate them into data science use cases. - Build robust data pipelines and use statistical and machine learning methods to drive insights. - Communicate complex technical findings in a clear, concise manner to both technical and non-technical audiences. - Mentor junior team members and contribute to knowledge sharing and best practices within the team. Required Skills And Qualifications : - Masters or PhD in Data Science, Computer Science, Operations Research, Applied Mathematics, or related fields. - Minimum 8 years of relevant experience in data science, with a strong focus on optimization. - Expertise in Python (NumPy, Pandas, SciPy, Scikit-learn), SQL, and optimization libraries such as PuLP, Pyomo, Gurobi, or CPLEX. - Experience with end-to-end lifecycle of internal optimization projects. - Strong analytical and problem-solving skills. - Excellent communication and stakeholder management abilities. Preferred Qualifications : - Experience working on internal company projects focused on logistics, resource planning, workforce optimization, or cost reduction. - Exposure to tools/platforms like Databricks, Azure ML, or AWS SageMaker. - Familiarity with dashboards and visualization tools like Power BI or Tableau. - Prior experience in consulting or internal centers of excellence (CoE) is a plus.

Role Summary : We are seeking a highly skilled Senior Data Science Consultant with 8+ years of experience to lead an internal optimization initiative. The ideal candidate should have a strong background in data science, operations research, and mathematical optimization, with a proven track record of applying these skills to solve complex business problems. This role requires a blend of technical depth, business acumen, and collaborative communication. A background in internal efficiency/operations improvement or cost/resource optimization projects is highly desirable. Key Responsibilities : - Lead and contribute to internal optimization-focused data science projects from design to deployment. - Develop and implement mathematical models to optimize resource allocation, process performance, and decision-making. - Use techniques such as linear programming, mixed-integer programming, heuristic and metaheuristic algorithms. - Collaborate with business stakeholders to gather requirements and translate them into data science use cases. - Build robust data pipelines and use statistical and machine learning methods to drive insights. - Communicate complex technical findings in a clear, concise manner to both technical and non-technical audiences. - Mentor junior team members and contribute to knowledge sharing and best practices within the team. Required Skills And Qualifications : - Masters or PhD in Data Science, Computer Science, Operations Research, Applied Mathematics, or related fields. - Minimum 8 years of relevant experience in data science, with a strong focus on optimization. - Expertise in Python (NumPy, Pandas, SciPy, Scikit-learn), SQL, and optimization libraries such as PuLP, Pyomo, Gurobi, or CPLEX. - Experience with end-to-end lifecycle of internal optimization projects. - Strong analytical and problem-solving skills. - Excellent communication and stakeholder management abilities. Preferred Qualifications : - Experience working on internal company projects focused on logistics, resource planning, workforce optimization, or cost reduction. - Exposure to tools/platforms like Databricks, Azure ML, or AWS SageMaker. - Familiarity with dashboards and visualization tools like Power BI or Tableau. - Prior experience in consulting or internal centers of excellence (CoE) is a plus.

Role Summary : We are seeking a highly skilled Senior Data Science Consultant with 8+ years of experience to lead an internal optimization initiative. The ideal candidate should have a strong background in data science, operations research, and mathematical optimization, with a proven track record of applying these skills to solve complex business problems. This role requires a blend of technical depth, business acumen, and collaborative communication. A background in internal efficiency/operations improvement or cost/resource optimization projects is highly desirable. Key Responsibilities : - Lead and contribute to internal optimization-focused data science projects from design to deployment. - Develop and implement mathematical models to optimize resource allocation, process performance, and decision-making. - Use techniques such as linear programming, mixed-integer programming, heuristic and metaheuristic algorithms. - Collaborate with business stakeholders to gather requirements and translate them into data science use cases. - Build robust data pipelines and use statistical and machine learning methods to drive insights. - Communicate complex technical findings in a clear, concise manner to both technical and non-technical audiences. - Mentor junior team members and contribute to knowledge sharing and best practices within the team. Required Skills And Qualifications : - Masters or PhD in Data Science, Computer Science, Operations Research, Applied Mathematics, or related fields. - Minimum 8 years of relevant experience in data science, with a strong focus on optimization. - Expertise in Python (NumPy, Pandas, SciPy, Scikit-learn), SQL, and optimization libraries such as PuLP, Pyomo, Gurobi, or CPLEX. - Experience with end-to-end lifecycle of internal optimization projects. - Strong analytical and problem-solving skills. - Excellent communication and stakeholder management abilities. Preferred Qualifications : - Experience working on internal company projects focused on logistics, resource planning, workforce optimization, or cost reduction. - Exposure to tools/platforms like Databricks, Azure ML, or AWS SageMaker. - Familiarity with dashboards and visualization tools like Power BI or Tableau. - Prior experience in consulting or internal centers of excellence (CoE) is a plus.

Looking for experienced Data Scientist Candidates. Job Description Leveraging knowledge in analytical and statistical algorithms to assist stakeholders in improving their business Partnering on the design and implementation of statistical data quality procedures for existing and new data sources Communicating complex data science solutions, concepts, and analyses to team members and business leaders Presenting data insights & recommendations to key stakeholders Establishing links across existing data sources and finding new, interesting data correlations Ensuring testing and validation are components of all analytics solutions Skills : Strong proficiency in predictive analytics, prescriptive analytics, AI, machine learning, and statistical modeling Proficiency in programming languages such as Python and SQL for data analysis and model development. Working with text data including Natural Language Processing (NLP) techniques such as tokenization, lemmatization, sentiment analysis, text classification, topic modeling, and entity recognition Hands-on experience with advanced AI techniques such as Retrieval-Augmented Generation (RAG), vector databases, and LLM integration for enhanced information retrieval and generation, GPT, and BERT Strong understanding of Machine Learning concepts including supervised and unsupervised learning, model training, evaluation, and deployment

Gen AI + DS + ML Ops Job Title: Generative AI and Data Science Engineer with MLOps Expertise Location: Gurgaon, India Employment Type: Full-time About the Role: We are seeking a versatile and highly skilled Generative AI and Data Science Engineer with strong MLOps expertise. This role combines deep technical knowledge in data science and machine learning with a focus on designing and deploying scalable, production-level AI solutions. You will work with cross-functional teams to drive AI/ML projects from research and prototyping through to deployment and maintenance, ensuring model robustness, scalability, and efficiency. Responsibilities: Generative AI Development and Data Science: Design, develop, and fine-tune generative AI models for various applications such as natural language processing, image synthesis, and data augmentation. Perform exploratory data analysis (EDA) and statistical modeling to identify trends, patterns, and actionable insights. Collaborate with data engineering and product teams to create data pipelines for model training, testing, and deployment. Apply data science techniques to optimize model performance and address real-world business challenges. Machine Learning Operations (MLOps): Implement MLOps best practices for managing and automating the end-to-end machine learning lifecycle, including model versioning, monitoring, and retraining. Build, maintain, and optimize CI/CD pipelines for ML models to streamline development and deployment processes. Ensure scalability, robustness, and security of AI/ML systems in production environments. Develop tools and frameworks for monitoring model performance and detecting anomalies post-deployment. Research and Innovation: Stay current with advancements in generative AI, machine learning, and MLOps technologies and frameworks. Identify new methodologies, tools, and technologies that could enhance our AI and data science capabilities. Engage in R&D initiatives and collaborate with team members on innovative projects. Requirements: Educational Background: Bachelors or Masters degree in Computer Science, Data Science, Engineering, or a related field. PhD is a plus. Technical Skills: Proficiency in Python and familiarity with machine learning libraries (e.g., TensorFlow, PyTorch, Keras, scikit-learn). Strong understanding of generative AI models (e.g., GANs, VAEs, transformers) and deep learning techniques. Experience with MLOps frameworks and tools such as MLflow, Kubeflow, Docker, and CI/CD platforms. Knowledge of data science techniques for EDA, feature engineering, statistical modeling, and model evaluation. Familiarity with cloud platforms (e.g., AWS, Google Cloud, Azure) for deploying and scaling AI/ML models. Soft Skills: Ability to collaborate effectively across teams and communicate complex technical concepts to non-technical stakeholders. Strong problem-solving skills and the ability to innovate in a fast-paced environment. Preferred Qualifications: Prior experience in designing and deploying large-scale generative AI models. Proficiency in SQL and data visualization tools (e.g., Tableau, Power BI). Experience with model interpretability and explainability frameworks.

Role Summary : We are seeking a highly skilled Senior Data Science Consultant with 8+ years of experience to lead an internal optimization initiative. The ideal candidate should have a strong background in data science, operations research, and mathematical optimization, with a proven track record of applying these skills to solve complex business problems. This role requires a blend of technical depth, business acumen, and collaborative communication. A background in internal efficiency/operations improvement or cost/resource optimization projects is highly desirable. Key Responsibilities : - Lead and contribute to internal optimization-focused data science projects from design to deployment. - Develop and implement mathematical models to optimize resource allocation, process performance, and decision-making. - Use techniques such as linear programming, mixed-integer programming, heuristic and metaheuristic algorithms. - Collaborate with business stakeholders to gather requirements and translate them into data science use cases. - Build robust data pipelines and use statistical and machine learning methods to drive insights. - Communicate complex technical findings in a clear, concise manner to both technical and non-technical audiences. - Mentor junior team members and contribute to knowledge sharing and best practices within the team. Required Skills And Qualifications : - Masters or PhD in Data Science, Computer Science, Operations Research, Applied Mathematics, or related fields. - Minimum 8 years of relevant experience in data science, with a strong focus on optimization. - Expertise in Python (NumPy, Pandas, SciPy, Scikit-learn), SQL, and optimization libraries such as PuLP, Pyomo, Gurobi, or CPLEX. - Experience with end-to-end lifecycle of internal optimization projects. - Strong analytical and problem-solving skills. - Excellent communication and stakeholder management abilities. Preferred Qualifications : - Experience working on internal company projects focused on logistics, resource planning, workforce optimization, or cost reduction. - Exposure to tools/platforms like Databricks, Azure ML, or AWS SageMaker. - Familiarity with dashboards and visualization tools like Power BI or Tableau. - Prior experience in consulting or internal centers of excellence (CoE) is a plus.

Role Summary : We are seeking a highly skilled Senior Data Science Consultant with 8+ years of experience to lead an internal optimization initiative. The ideal candidate should have a strong background in data science, operations research, and mathematical optimization, with a proven track record of applying these skills to solve complex business problems. This role requires a blend of technical depth, business acumen, and collaborative communication. A background in internal efficiency/operations improvement or cost/resource optimization projects is highly desirable. Key Responsibilities : - Lead and contribute to internal optimization-focused data science projects from design to deployment. - Develop and implement mathematical models to optimize resource allocation, process performance, and decision-making. - Use techniques such as linear programming, mixed-integer programming, heuristic and metaheuristic algorithms. - Collaborate with business stakeholders to gather requirements and translate them into data science use cases. - Build robust data pipelines and use statistical and machine learning methods to drive insights. - Communicate complex technical findings in a clear, concise manner to both technical and non-technical audiences. - Mentor junior team members and contribute to knowledge sharing and best practices within the team. Required Skills And Qualifications : - Masters or PhD in Data Science, Computer Science, Operations Research, Applied Mathematics, or related fields. - Minimum 8 years of relevant experience in data science, with a strong focus on optimization. - Expertise in Python (NumPy, Pandas, SciPy, Scikit-learn), SQL, and optimization libraries such as PuLP, Pyomo, Gurobi, or CPLEX. - Experience with end-to-end lifecycle of internal optimization projects. - Strong analytical and problem-solving skills. - Excellent communication and stakeholder management abilities. Preferred Qualifications : - Experience working on internal company projects focused on logistics, resource planning, workforce optimization, or cost reduction. - Exposure to tools/platforms like Databricks, Azure ML, or AWS SageMaker. - Familiarity with dashboards and visualization tools like Power BI or Tableau. - Prior experience in consulting or internal centers of excellence (CoE) is a plus.

Role Summary : We are seeking a highly skilled Senior Data Science Consultant with 8+ years of experience to lead an internal optimization initiative. The ideal candidate should have a strong background in data science, operations research, and mathematical optimization, with a proven track record of applying these skills to solve complex business problems. This role requires a blend of technical depth, business acumen, and collaborative communication. A background in internal efficiency/operations improvement or cost/resource optimization projects is highly desirable. Key Responsibilities : - Lead and contribute to internal optimization-focused data science projects from design to deployment. - Develop and implement mathematical models to optimize resource allocation, process performance, and decision-making. - Use techniques such as linear programming, mixed-integer programming, heuristic and metaheuristic algorithms. - Collaborate with business stakeholders to gather requirements and translate them into data science use cases. - Build robust data pipelines and use statistical and machine learning methods to drive insights. - Communicate complex technical findings in a clear, concise manner to both technical and non-technical audiences. - Mentor junior team members and contribute to knowledge sharing and best practices within the team. Required Skills And Qualifications : - Masters or PhD in Data Science, Computer Science, Operations Research, Applied Mathematics, or related fields. - Minimum 8 years of relevant experience in data science, with a strong focus on optimization. - Expertise in Python (NumPy, Pandas, SciPy, Scikit-learn), SQL, and optimization libraries such as PuLP, Pyomo, Gurobi, or CPLEX. - Experience with end-to-end lifecycle of internal optimization projects. - Strong analytical and problem-solving skills. - Excellent communication and stakeholder management abilities. Preferred Qualifications : - Experience working on internal company projects focused on logistics, resource planning, workforce optimization, or cost reduction. - Exposure to tools/platforms like Databricks, Azure ML, or AWS SageMaker. - Familiarity with dashboards and visualization tools like Power BI or Tableau. - Prior experience in consulting or internal centers of excellence (CoE) is a plus.

Role Summary : We are seeking a highly skilled Senior Data Science Consultant with 8+ years of experience to lead an internal optimization initiative. The ideal candidate should have a strong background in data science, operations research, and mathematical optimization, with a proven track record of applying these skills to solve complex business problems. This role requires a blend of technical depth, business acumen, and collaborative communication. A background in internal efficiency/operations improvement or cost/resource optimization projects is highly desirable. Key Responsibilities : - Lead and contribute to internal optimization-focused data science projects from design to deployment. - Develop and implement mathematical models to optimize resource allocation, process performance, and decision-making. - Use techniques such as linear programming, mixed-integer programming, heuristic and metaheuristic algorithms. - Collaborate with business stakeholders to gather requirements and translate them into data science use cases. - Build robust data pipelines and use statistical and machine learning methods to drive insights. - Communicate complex technical findings in a clear, concise manner to both technical and non-technical audiences. - Mentor junior team members and contribute to knowledge sharing and best practices within the team. Required Skills And Qualifications : - Masters or PhD in Data Science, Computer Science, Operations Research, Applied Mathematics, or related fields. - Minimum 8 years of relevant experience in data science, with a strong focus on optimization. - Expertise in Python (NumPy, Pandas, SciPy, Scikit-learn), SQL, and optimization libraries such as PuLP, Pyomo, Gurobi, or CPLEX. - Experience with end-to-end lifecycle of internal optimization projects. - Strong analytical and problem-solving skills. - Excellent communication and stakeholder management abilities. Preferred Qualifications : - Experience working on internal company projects focused on logistics, resource planning, workforce optimization, or cost reduction. - Exposure to tools/platforms like Databricks, Azure ML, or AWS SageMaker. - Familiarity with dashboards and visualization tools like Power BI or Tableau. - Prior experience in consulting or internal centers of excellence (CoE) is a plus.

Experience: 7-12years Location and Work Mode: Pune Job Description: About this Role We are seeking a highly skilled and motivated Data Scientist to join our team. This role is ideal for individuals who are passionate about leveraging data to drive innovation and create intelligent, scalable solutions. The successful candidate will work across a variety of data science domains, including diagnostic, predictive, and prescriptive analytics, and will contribute to the development of autonomous cognitive systems. This is an exciting opportunity to be part of a forward-thinking team that values continuous learning and collaboration. Who are you A data enthusiast with a strong foundation in machine learning, deep learning, and statistical modelling. A collaborative problem-solver who thrives in cross-functional teams and is comfortable engaging with stakeholders. A continuous learner with a passion for exploring new tools, technologies, and methodologies. An effective communicator who can translate complex data insights into actionable business strategies. A self-starter with a proactive mindset and the ability to work independently in a dynamic environment. What you will do Manage and process large-scale data on both on-premise and cloud platforms (preferably AWS). Design and implement diagnostic models using decision theory and causal inference techniques (e.g., DAG, ADMG, Deterministic SME). Build and productise diagnostic systems for scalable reuse across the organisation. Develop robust predictive and prescriptive analytics models using AI techniques such as ML, DL, NLP, ES, and RL. Create intelligent systems that determine the Next Best Action based on prescriptive analytics. Drive the development of autonomous cognitive systems that proactively recommend actions with minimal human intervention. Apply advanced deep learning techniques including CNNs, RNNs, and MLPs to solve complex business problems. Utilise machine learning and deep learning libraries such as TensorFlow, PyTorch, Scikit-learn, NumPy, Pandas, Statsmodels, Theano, and XGBoost. Collaborate with stakeholders to understand business needs and deliver data-driven solutions. Present insights and findings using visualisation tools like Tableau and Power BI. What skills you need Proficiency in programming languages: Python, R, SQL Experience with frameworks: TensorFlow, Keras, Scikit-learn Strong understanding of statistical modelling: regression, classification, clustering, time series Hands-on experience with cloud platforms: AWS (preferred), Azure Familiarity with big data technologies and environments Excellent communication and stakeholder management skills Strong analytical and problem-solving abilities At least one certification in AWS is preferred What skills you will learn Advanced applications of causal inference and decision theory in real-world scenarios Building and deploying scalable AI systems in cloud environments Designing autonomous systems that integrate feedback loops for continuous learning Enhancing stakeholder engagement through data storytelling and visualisation Exposure to cutting-edge tools and frameworks in the AI and ML ecosystem

Experience: Minimum 10+ years in AI/ML or data science, with at least 5 years in a leadership role. Proven experience in banking or financial services is highly preferred. Hands-on with AI/ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn) and tools (Python, SQL, Spark). Experience in Azure ML tools: Databricks etc. Experience with end-to-end model lifecycle management and MLOps. Minimum Qualification: Masters Degree/PhD in Computer Science, Econometrics, Statistics, or related fields.

Notice Period : Immediate - 15 Days About the Role : We are seeking a highly skilled Senior Data Scientist to join our team and contribute to cutting-edge projects. As a key member of our data science team, you will leverage your expertise in machine learning, natural language processing, and data engineering to develop innovative solutions that drive business value. Responsibilities : - Machine Learning Model Development : Design, develop, and deploy advanced machine learning models, focusing on natural language processing tasks such as text classification, sentiment analysis, and language generation. - Data Engineering : Extract, transform, and load (ETL) data from various sources, ensuring data quality and consistency. - NLP Techniques : Apply state-of-the-art NLP techniques, including language models and text processing, to solve complex problems. - Python and ML Frameworks : Utilize Python programming language and popular ML frameworks like PyTorch or TensorFlow to build efficient and scalable models. - Cloud and Containerization : Leverage cloud platforms (GCP, AWS) and containerization technologies (Docker) for efficient deployment and management of ML models. - Database Management : Work with relational databases (Postgres, MySQL) to store, manage, and query large datasets. - Knowledge Graphs and ML Publications : Contribute to the development of knowledge graphs and stay updated with the latest advancements in the field through research and publications. Qualifications : Experience : 4-7 years of hands-on experience in data science, with a strong focus on machine learning and natural language processing. Technical Skills : - Proficiency in Python programming language. - Deep understanding of machine learning algorithms and techniques. - Expertise in NLP, including language models and text processing. - Familiarity with ML frameworks like PyTorch or TensorFlow. - Experience with cloud platforms (GCP, AWS) and containerization (Docker). - Knowledge of relational databases (Postgres, MySQL). Soft Skills : - Strong problem-solving and analytical skills. - Excellent communication and collaboration abilities. - Ability to work independently and as part of a team.

Role & responsibilities Develop and implement a comprehensive analytics strategy to support the organization's business objectives. Lead cross-functional projects using advanced data modeling and analysis techniques to discover insights that will guide strategic decisions and uncover optimization opportunities. Build, develop and maintain data models, reporting systems, data automation systems, dashboards and performance metrics support that support key business decisions on Microsoft Power BI and Snowflake. Driving key business impacting processes like demand forecast generation and SNOP processes. Generating sales recommendation for trade sales team. Optimizing business process like network, inventory, etc., with data modeling and predicting / prescribing algorithms. Oversee the design and delivery of reports and insights that analyze business functions and key operations and performance metrics. Manage and optimize processes for data intake, validation, mining and engineering as well as modeling, visualization and communication deliverables. Anticipate future demands of initiatives related to people, technology, budget and business within your department and design/implement solutions to meet these needs. Apply advanced analytics techniques to improve commercial routines and processes. Organize and drive successful completion of data insight initiatives through effective management of analyst and data employees and effective collaboration with stakeholders. Communicate results and business impacts of insight initiatives to stakeholders within and outside of the company. Ability to look, analyse, critically think, and communicate insights to support data-driven decisions. Preferred candidate profile With 10+ years of experience in a position monitoring, managing, manipulating and drawing insights from data, and someone with at least 3 years of experience leading a team Experience with data visualization tools: Power BI, Tableau, Raw, chart.js, etc. Experience in understanding and managing the data flow across multiple systems to datawarehouse. Working knowledge of data mining principles: predictive analytics, mapping, collecting data from multiple data systems on premises and cloud-based data sources. Understanding of and experience using analytical concepts and statistical techniques: hypothesis development, designing tests/experiments, analyzing data, drawing conclusions, and developing actionable recommendations for business units.