3471 Data Scientist Jobs - Page 31

Responsibilities & Key Deliverables We are looking for a Senior Data Scientist with a balanced mix of hands-on expertise and team leadership capabilities. The ideal candidate is someone who thrives at the intersection of technical depth and strategic impact. In this dual role, you'll own critical projects end-to-end while mentoring a team of data scientists and analysts to drive enterprise-wide AI initiatives. Leadership (50%) Lead and mentor a small team of junior to mid-level data scientists and analysts. Translate high-level business problems into analytical frameworks and guide project execution. Review models, code, and outputs to ensure quality and scalability. Manage timelines, prioritize tasks, and align with cross-functional stakeholders. Collaborate with product, engineering, and business teams to deliver AI-driven solutions. Individual Contributor (50%) Design, build, and deploy machine learning models, statistical frameworks, and data pipelines. Perform deep data exploration and generate actionable insights. Work on a range of problems including predictive modeling, segmentation, recommendation systems, NLP, and computer vision depending on project needs. Conduct robust feature engineering, model evaluation, and tuning. Communicate findings clearly to technical and non-technical stakeholders. Experience 5–8 years of hands-on experience in data science, machine learning, or analytics. Qualifications Required Qualifications: Strong programming skills in Python, SQL, and proficiency with libraries like scikit-learn, TensorFlow, PyTorch, or XGBoost. Solid understanding of supervised/unsupervised ML, A/B testing, and statistical modeling. Demonstrated experience in leading or mentoring data science teams (formal or informal). Excellent communication, problem-solving, and stakeholder engagement skills. Experience working with both structured and unstructured data at scale. Good to Have: Exposure to cloud-based AI/ML platforms such as AWS SageMaker, Google Vertex AI, or Azure ML Studio. Experience working with cloud-native data tools (e.g., BigQuery, Redshift, Snowflake). Understanding of data architecture and modern database systems (e.g., PostgreSQL, MongoDB, Cassandra). Familiarity with MLOps practices, model monitoring, and CI/CD pipelines for ML. Job Segment: Machinist, Engineer, Scientific, Manufacturing, Engineering

We are on the lookout for a Data Scientist with a deep focus on Large Language Models (LLM), General AI, and specialized knowledge in deploying these technologies via APIs using Flask, FastAPI, or Django. This role requires a keen understanding of the latest in AI, including familiarity with Langchain and LlamaIndex for advanced LLM deployment. The ideal candidate will lead our efforts in leveraging LLM for innovative applications, ensuring scalable and efficient model deployment. Responsibilities Lead the development and deployment of LLM and General AI models, focusing on scalable solutions. Specialize in API development for LLM deployment using Flask, FastAPI, or Django, ensuring seamless integration into our products. Design, construct, install, test, and maintain highly scalable data management systems, ensuring robust data pipelines for AI deployments. Implement data ingestion routines both from within and outside the company, ensuring data quality and accessibility for advanced analytics. Demonstrate a deep understanding of Langchain and LlamaIndex for cutting-edge LLM applications. Collaborate with product teams and stakeholders to implement AI-driven solutions that meet business needs. Stay updated with AI advancements, particularly in LLM and deployment methodologies, to keep our solutions innovative. Qualifications Expertise in LLM, General AI, and the deployment of AI models. Strong experience in API development with Flask, FastAPI, or Django. Knowledge of Langchain and LlamaIndex for LLM applications. Expertise in AI and ML development tools, frameworks, and libraries (TensorFlow, PyTorch, GPT, etc.). Proven ability in data engineering, including managing data pipelines, databases, and real-time data processing systems. Proficient in Python and familiar with AI/ML libraries and frameworks. Innovative thinker with excellent problem-solving capabilities. BSc/BA in Computer Science, Engineering, or related; a graduate degree in a relevant area is highly preferred.

Experience: 5 to 7 years Location: Bengaluru, Gurgaon, Pune Job code: 101284 Posted on: Jul 22, 2025 About Us: AceNet Consulting is a fast-growing global business and technology consulting firm specializing in business strategy, digital transformation, technology consulting, product development, start-up advisory and fund-raising services to our global clients across banking & financial services, healthcare, supply chain & logistics, consumer retail, manufacturing, eGovernance and other industry sectors. We are looking for hungry, highly skilled and motivated individuals to join our dynamic team. If you’re passionate about technology and thrive in a fast-paced environment, we want to hear from you. Job Summary: We are seeking a skilled and innovative Data Scientist to join our team and help drive data-informed decision-making across the organization. The ideal candidate will be responsible for collecting, analyzing, and interpreting large and complex datasets to uncover actionable insights and develop predictive models. You will work closely with cross-functional teams to design data-driven solutions that solve real business problems, improve processes, and support strategic initiatives. Key Responsibilities: Experience working closely with other data scientists, data engineers software engineers, data managers and business partners. Can build scalable, re-usable, impactful data science products, usually containing statistical or machine learning algorithms, in collaboration with data engineers and software engineers. Can carry out data analyses to yield actionable business insights. Applied knowledge of data science tools and approaches across all data lifecycle stages. Thorough understanding of underlying mathematical foundations of statistics and machine learning. Development experience in one or more object-oriented programming languages (e.g. Python, Go, Java, C++) Advanced SQL knowledge. Knowledge of experimental design and analysis. Customer-centric and pragmatic mindset. Focus on value delivery and swift execution, while maintaining attention to detail. Strong software engineering and ML system design experience. Role Requirements and Qualifications: Hands-on experience (typically 5+ years) designing, planning, prototyping, productionizing, maintaining and documenting reliable and scalable data science products in complex environments. Strong Python and intermediate SQL skills. Experience building, deploying, and evaluating ML/NLP/GenAI systems. Experience with ML system design. Very strong (including written) communication skills and ability to break down and articulate complex tasks into implementation strategies. Software engineering best practices, including testing, OOP, etc. Knowledge of cloud systems, especially azure preferred. Experience with system designs like kNN model, NLP algorithms. A more traditional ML perspective, some knowledge and understanding of mathematical optimizers, how to select the best ones for purpose and set parameters. Why Join Us: Opportunities to work on transformative projects, cutting-edge technology and innovative solutions with leading global firms across industry sectors. Continuous investment in employee growth and professional development with a strong focus on up & re-skilling. Competitive compensation & benefits, ESOPs and international assignments. Supportive environment with healthy work-life balance and a focus on employee well-being. Open culture that values diverse perspectives, encourages transparent communication and rewards contributions. How to Apply: If you are interested in joining our team and meet the qualifications listed above, please apply and submit your resume highlighting why you are the ideal candidate for this position.

About Snapmint: India’s booming consumer market has over 300 million credit-eligible consumers, yet only 35million actively use credit cards. At Snapmint, we are building a better alternative to credit cards that lets consumers buy now and pay later for a wide variety of products, be it shoes, clothes, fashion accessories, clothes or mobile phones. We firmly believe that an enduring financial services business must be built on the bedrock of providing honest, transparent and fair terms. Founded in 2017, today we are the leading online zero-cost EMI provider in India. We have served over 10M consumers across 2,200 cities and are doubling year on year. Our founders are serial entrepreneurs and alumni of IIT Bombay and ISB with over two decades of experience across leading organizations like Swiggy, Oyo, Maruti Suzuki and ZS Associates before successfully scaling and exiting businesses in patent analytics, ad-tech and bank-tech software services. Role Overview: We are seeking a Data Scientist with 2–3 years of experience to build and deploy machine learning models in the fintech domain. The role involves working on credit risk, fraud detection, and customer analytics using advanced statistical techniques and scalable data platforms. The ideal candidate should demonstrate strong technical proficiency and the ability to translate data insights into actionable business outcomes. Key Responsibilities: Build, deploy, and maintain machine learning models for: Credit underwriting & credit scoring Fraud detection & transaction monitoring Customer lifetime value prediction Pricing & offer personalization Collections optimization Design experiments and A/B tests to measure the effectiveness of BNPL products and features. Conduct exploratory data analysis to identify business insights and opportunities. Collaborate with data engineering to ensure robust data pipelines, feature stores, and model monitoring systems. Translate complex data science solutions into actionable business recommendations. Continuously improve model accuracy, fairness, and interpretability. Requirements: Bachelor’s degree in Engineering 2-3 years of experience in data science or machine learning (fintech or financial services is a plus). Strong programming skills in Python, SQL. Experience in Java is a plus. Experience with ML libraries (scikit-learn, XGBoost, LightGBM, TensorFlow, PyTorch, etc.) Familiarity with risk modeling, credit scoring techniques, and time series forecasting. Understanding of statistical techniques like hypothesis testing, regression, clustering, survival analysis, etc. Experience working with large-scale data in cloud platforms (AWS, GCP, Azure). Strong communication skills with ability to simplify complex concepts for business stakeholders. Location: Bangalore Working days: Monday - Friday

Job Summary: We are seeking a proactive and detail-oriented Data Scientist to join our team and contribute to the development of intelligent AI-driven production scheduling solutions. This role is ideal for candidates passionate about applying machine learning, optimization techniques, and operational data analysis to enhance decision-making and drive efficiency in manufacturing or process industries. You will play a key role in designing, developing, and deploying smart scheduling algorithms integrated with real-world constraints like machine availability, workforce planning, shift cycles, material flow, and due dates. Experience: 1 Year Responsibilities: 1. AI-Based Scheduling Algorithm Development Develop and refine scheduling models using: Constraint Programming Mixed Integer Programming (MIP) Metaheuristic Algorithms (e.g., Genetic Algorithm, Ant Colony, Simulated Annealing) Reinforcement Learning or Deep Q-Learning Translate shop floor constraints (machines, manpower, sequence dependencies, changeovers) into mathematical models. Create simulation environments to test scheduling models under different scenarios. 2. Data Exploration & Feature Engineering Analyze structured and semi-structured production data from MES, SCADA, ERP, and other sources. Build pipelines for data preprocessing, normalization, and handling missing values. Perform feature engineering to capture important relationships like setup times, cycle duration, and bottlenecks. 3. Model Validation & Deployment Use statistical metrics and domain KPIs (e.g., throughput, utilization, makespan, WIP) to validate scheduling outcomes. Deploy solutions using APIs, dashboards (Streamlit, Dash), or via integration with existing production systems. Support ongoing maintenance, updates, and performance tuning of deployed models. 4. Collaboration & Stakeholder Engagement Work closely with production managers, planners, and domain experts to understand real-world constraints and validate model results. Document solution approaches, model assumptions, and provide technical training to stakeholders. Qualifications: Bachelor’s or Master’s degree in: Data Science, Computer Science, Industrial Engineering, Operations Research, Applied Mathematics, or equivalent. Minimum 1 year of experience in data science roles with exposure to: AI/ML pipelines, predictive modelling, Optimization techniques or industrial scheduling Proficiency in Python, especially with: pandas, numpy, scikit-learn ortools, pulp, cvxpy or other optimization libraries, matplotlib, plotly for visualization Solid understanding of: Production planning & control processes (dispatching rules, job-shop scheduling, etc.), Machine Learning fundamentals (regression, classification, clustering) Familiarity with version control (Git), Jupyter/VSCode environments, and CI/CD principles Preferred (Nice-to-Have) Skills: Experience with: Time-series analysis, sensor data, or anomaly detection, Manufacturing execution systems (MES), SCADA, PLC logs, or OPC UA data, Simulation tools (SimPy, Arena, FlexSim) or digital twin technologies Exposure to containerization (Docker) and model deployment (FastAPI, Flask) Understanding of lean manufacturing principles, Theory of Constraints, or Six Sigma Soft Skills: Strong problem-solving mindset with ability to balance technical depth and business context. Excellent communication and storytelling skills to convey insights to both technical and non-technical stakeholders. Eagerness to learn new tools, technologies, and domain knowledge.

Location : Ahmedabad Work Mode : Work From Office Working Days : 5.5 working days a week We’re looking for a talented Data Scientist enthusiast who uses analytical, statistical, and programming skills to collect large data sets & develop data-driven solutions. Technical Skills:  Language: Python  Proficiency in data mining, mathematics, and statistical analysis  Machine learning techniques and algorithms, with good expertise in optimization  Cloud: GCP (Preferred) /Azure  Data-oriented personality Ideally, you should have: 04 to 06 years of proven experience as a Data Scientist  Identify valuable data sources and automate collection processes  Undertake preprocessing of structured and unstructured data  Analyze large amounts of information to discover trends and patterns  Run optimization algorithms to identify the best solution (Linear Programming expertise required)  Build predictive models and machine-learning algorithms  Combine models through ensemble modeling  Present information using data visualization techniques  Proficiency in Python and Machine Learning.  Experience with Generative AI and Agentic AI models.  Strong analytical mind and business acumen.  Excellent problem-solving aptitude.  Effective communication and presentation skills.  Knowledge of the Indian power sector will be a definite plus

Job Description We are seeking for a Data Scientist/ML Engineer with experience in NLP, statistics, and Conversational AI. The ideal candidate is adept at using Statistical Modelling, Machine learning algorithms and Conversational AI. Strong experience using variety of data mining/ Machine Learning methods, using/coding algorithms and running simulations. The right candidate will have a passion for discovering solutions hidden in large data sets and working with business partners to improve business outcomes. Minimum Qualifications Skills and Qualifications: Doctorate (Academic) Degree with 0 years industry experience; Master's Level Degree and related work experience of 3 years; Bachelor's Level Degree and related work experience of 5 years in computer science, statistics, applied mathematics, or related discipline Experience solving problems with Conversational AI in a production environment for a High-tech Manufacturing Industry Experience in Python and ML packages (NumPy, Keras, Seaborn, Scikit-learn). Excellent understanding of machine learning techniques and algorithms such as, Regression models, kNN, SVM,NB, Decision Trees. Expertise/Familiarity with one or more deep learning frameworks such as TensorFlow, PyTorch. Responsibilities for Data Scientist/ML Engineer: Building end-to-end ML systems (Including traditional ML models and Conversational AI) and deploying them to operate at scale. Research and devise innovative statistical models/ML models for data analysis Develop and maintain RAG (Retrieval-Augmented Generation) applications. Implement changes to algorithms to improve AI performance and retrieval techniques. Use predictive modeling to increase and optimize customer service experience and supply chain optimization. Identify patterns in data using statistical modeling, develop custom data models and algorithms to apply to data sets. Work with business partners throughout the organization to find opportunities for using company data to drive solutions. Working with project managers to establish objectives for AI systems.

Role Type : Data Specialist Experience : 4+ Years Location : Bangalore Notice Period : Immediate to 15 Days Work Mode : 5 Days (WFO) Candidate should be available to take F2F in Bangalore Key Responsibilities Design and build scalable machine learning models to solve real-world business problems. Translate business requirements into clear analytical solutions using data science techniques. Write optimized SQL queries to extract, manipulate, and analyze large datasets. Develop and deploy production-ready code using Python. Collaborate with data engineers, product managers, and business stakeholders to build end-to-end data products. Communicate complex findings in a clear, concise manner to non-technical stakeholders. Continuously monitor and improve the performance of deployed models. Mentor junior data scientists and review their code/models as needed. Requirements/Skill sets Bachelor's or Master’s degree in Computer Science, Statistics, Mathematics, Engineering, or a related field. 4+ years of hands-on experience in data science, analytics, or machine learning. Expert proficiency in Python , including libraries like pandas, scikit-learn, NumPy, etc. Strong experience in SQL for data extraction and transformation. Proven ability to build and evaluate supervised and unsupervised ML models. Experience with model deployment, version control (e.g., Git), and working in cloud environments (AWS/GCP/Azure). Excellent problem-solving skills and attention to detail. Strong communication and collaboration skills.

Experience: 5+ years Location: Chennai (Work from Office preferred) Joining: Immediate preferred Key Responsibilities: Design and implement LLM-powered solutions including Retrieval-Augmented Generation (RAG) workflows Fine-tune, prompt-engineer, and evaluate large language models for specific business use cases Collaborate with product and engineering teams to integrate AI modules into production applications Analyze large, unstructured datasets and derive meaningful insights Stay updated on emerging trends in GenAI, foundation models, and open-source LLMs Must-Have Skills: Strong understanding of LLMs (OpenAI, Cohere, HuggingFace models, etc.) Hands-on experience with RAG pipelines , vector databases (FAISS, Pinecone, etc.), and retrieval strategies Proficient in Python and machine learning libraries (Transformers, LangChain, PyTorch/TensorFlow) Experience in data preprocessing , model evaluation , and deployment of NLP solutions Ability to translate business requirements into scalable ML solutions Good to Have: Knowledge of cloud platforms (AWS/GCP/Azure) Exposure to MLOps workflows and LLMOps tools Experience with open-source LLMs (LLaMA, Mistral, etc.) What We Offer: Opportunity to work on impactful AI projects Collaborative and innovative environment Competitive compensation and growth opportunities Job Types: Full-time, Freelance Pay: ₹700,000.00 - ₹1,300,000.00 per year Benefits: Health insurance Schedule: Day shift Work Location: In person Expected Start Date: 28/07/2025

You will be joining a forward-thinking team at Tecblic, a company specializing in delivering AI-driven solutions to empower businesses in the digital age. If you are passionate about Large Language Models (LLMs), machine learning, and pushing the boundaries of Agentic AI, we welcome you to be a part of our innovative team. As a Machine Learning Engineer at Tecblic, your key responsibilities will include conducting research and development to design and fine-tune machine learning models, with a specific focus on LLMs and Agentic AI systems. You will be responsible for optimizing pre-trained LLMs for domain-specific use cases, collaborating with software engineers and product teams to integrate AI models into customer-facing applications, and performing data preprocessing, pipeline creation, feature engineering, and exploratory data analysis for dataset preparation. Additionally, you will design and implement model deployment pipelines, prototype innovative solutions using cutting-edge techniques, and provide technical mentorship to junior team members. In terms of core technical skills, we require proficiency in Python for machine learning and data science tasks, expertise in ML frameworks and libraries like PyTorch, TensorFlow, and Hugging Face, a solid understanding of LLMs such as GPT, T5, BERT, or Bloom, experience in NLP tasks, knowledge of deep learning architectures, strong data manipulation skills, and familiarity with cloud services and ML model deployment tools. Exposure to Agentic AI, MLOps tools, generative AI models, prompt engineering, few-shot/fine-tuned approaches for LLMs, vector databases, version control, and collaborative development practices would be considered advantageous. Furthermore, we are looking for individuals with a strong analytical and mathematical background, including proficiency in linear algebra, statistics, and probability, as well as a solid understanding of algorithms and data structures to solve complex ML problems. Soft skills such as excellent problem-solving, critical-thinking, communication, collaboration, self-motivation, and continuous learning mindset are also highly valued. If you are ready to contribute your expertise and passion for machine learning and AI to a dynamic and innovative team, Tecblic is the place for you. Join us in pushing the boundaries of technology and creating impactful AI-driven solutions for businesses in the digital era.,

We are looking for a highly analytical and experienced Data Scientist to join our team. As a Data Scientist, you will be responsible for analyzing large datasets, identifying trends, and building data products to extract valuable business insights. If you have a passion for turning raw data into actionable intelligence and possess strong analytical and problem-solving skills, we invite you to apply. Your responsibilities will include identifying valuable data sources and automating collection processes, implementing NLP algorithms for extracting insights from unstructured data, preprocessing structured and unstructured data, exploring innovative deep learning approaches, analyzing information to discover trends, building predictive models and machine-learning algorithms, utilizing ensemble modeling techniques, presenting information using data visualization, and proposing solutions to address business challenges. Collaboration with engineering and product development teams will be key. To be successful in this role, you should have proven experience as a Data Scientist, expertise in applying machine learning, NLP, computer vision, and deep learning techniques, proficiency in programming languages such as R, SQL, and Python, experience with business intelligence tools and data frameworks, strong math skills, exceptional problem-solving aptitude, and excellent communication and presentation skills. A B.Tech in Computer Science or a related quantitative field is preferred.,

DATA SCIENTISTS FOR OUR MNC CLIENT 100% REMOTE APPLICABLE POSITIONS: 9 ONLY IMMEDIATE JOINERS BGV IS MUST MUST 7 to 12 years -HAVING TITLE AS data scientist/senior data scientist job title - Key skills: python/power bi/AI/ML/client handling Required Candidate profile MUST : 7 to 12 years -HAVING TITLE AS data scientist/senior data scientist job title - Key skills: python/power bi/AI/ML/client handling - remote ONLY IMMEDIATE JOINERS YOHI@AXYCUBE.IN /9108687980

Role & responsibilitie Roles and Responsibilities: Deep understanding of statistical and machine learning models. Proven experience building models and placing models into production. Supporting implementation of advanced analytics in industry Resolving issues at Data Platform. Strong experience on VNF, Kr8 Platforms. Experience with big data: extraction, processing, filtering, and presenting large data quantities (100K to Millions of rows) via Cloud technologies, SQL, and data pipelines. Experience in optimization problems, and solving those problems at scale Presenting information using data visualization techniques Identify valuable data sources and automate collection processes Analyse large amounts of information to discover trends and patterns Build predictive models and machine-learning algorithms Combine models through ensemble modelling Propose solutions and strategies to business challenges Collaborate across different business unit and product development teams s Preferred candidate profile Strong Skills of machine-learning and AI Strong Knowledge of Python, PySpark, SQL, Flask; familiarity with data frameworks such as Hadoop, databases (PostgreSQL, MongoDB, YugaByte), understanding of cloud-native deployments and infrastructure Strong math / analytical skills (e.g. statistics, algebra) Excellent communication and presentation skills MSc/BSc/BA in Computer Science, Engineering or relevant field; graduate degree in Data Science or a quantitative field is preferred Experience in data mining Experience in product development

As a Senior Data Scientist with 5+ years of experience, you will play a crucial role in our team based in Indore/Pune. Your responsibilities will involve designing and implementing models, extracting insights from data, and interpreting complex data structures to facilitate business decision-making. You should have a strong background in Machine Learning areas such as Natural Language Processing, Machine Vision, Time Series, etc. Your expertise should extend to Model Tuning, Model Validation, Supervised and Unsupervised Learning. Additionally, hands-on experience with model development, data preparation, and deployment of models for training and inference is essential. Proficiency in descriptive and inferential statistics, hypothesis testing, and data analysis and exploration are key skills required for this role. You should be adept at developing code that enables reproducible data analysis. Familiarity with AWS services like Sagemaker, Lambda, Glue, Step Functions, and EC2 is expected. Knowledge of data science code development and deployment IDEs such as Databricks, Anaconda distribution, and similar tools is essential. You should also possess expertise in ML algorithms related to time-series, natural language processing, optimization, object detection, topic modeling, clustering, and regression analysis. Your skills should include proficiency in Hive/Impala, Spark, Python, Pandas, Keras, SKLearn, StatsModels, Tensorflow, and PyTorch. Experience with end-to-end model deployment and production for at least 1 year is required. Familiarity with Model Deployment in Azure ML platform, Anaconda Enterprise, or AWS Sagemaker is preferred. Basic knowledge of deep learning algorithms like MaskedCNN, YOLO, and visualization and analytics/reporting tools such as Power BI, Tableau, Alteryx would be advantageous for this role.,

Job Description: 1. Be a hands on problem solver with consultative approach, who can apply Machine Learning & Deep Learning algorithms to solve business challenges a. Use the knowledge of wide variety of AI/ML techniques and algorithms to find what combinations of these techniques can best solve the problem b. Improve Model accuracy to deliver greater business impact c. Estimate business impact due to deployment of model 2. Work with the domain/customer teams to understand business context , data dictionaries and apply relevant Deep Learning solution for the given business challenge 3. Working with tools and scripts for sufficiently pre-processing the data & feature engineering for model development – Python / R / SQL / Cloud data pipelines 4. Design , develop & deploy Deep learning models using Tensorflow / Pytorch 5. Experience in using Deep learning models with text, speech, image and video data a. Design & Develop NLP models for Text Classification, Custom Entity Recognition, Relationship extraction, Text Summarization, Topic Modeling, Reasoning over Knowledge Graphs, Semantic Search using NLP tools like Spacy and opensource Tensorflow, Pytorch, etc b. Design and develop Image recognition & video analysis models using Deep learning algorithms and open source tools like OpenCV c. Knowledge of State of the art Deep learning algorithms 6. Optimize and tune Deep Learnings model for best possible accuracy 7. Use visualization tools/modules to be able to explore and analyze outcomes & for Model validation eg: using Power BI / Tableau 8. Work with application teams, in deploying models on cloud as a service or on-prem a. Deployment of models in Test / Control framework for tracking b. Build CI/CD pipelines for ML model deployment 9. Integrating AI&ML models with other applications using REST APIs and other connector technologies 10. Constantly upskill and update with the latest techniques and best practices. Write white papers and create demonstrable assets to summarize the AIML work and its impact.

Role & responsibilities - Strong knowledge in OOPs and creating custom python packages for serverless applications. Strong Knowledge in SQL querying. Hands on experience in AWS services like Lambda, EC2, EMR, S3 and Athena, Batch, Textract and Comprehend. Strong Expertise in extracting text, tables, logos from low quality scanned multipage pdfs (80 - 150 dpi) and Images. Good Understanding in Probability and Statistics concepts and ability to find hidden patterns, relevant insights from the data. Knowledge in applying state of art NLP models like BERT, GPT - x, sciSpacy, Bidirectional LSTMs-CNN, RNN, AWS medical Comprehend for Clinical Named Entity Recognition (NER). Strong Leadership Skills. Deployment of custom trained and prebuilt NER models using AWS Sagemaker. Knowledge in setting up AWS Textract pipeline for large scale text processing using AWS SNS, AWS SQS, Lambda and EC2. Should have Intellectual curiosity to learn new things. ISMS responsibilities should be followed as per company policy. Preferred candidate profile - 3+ years Hands on in Python and data science like tools pandas, NumPy, SciPy, matplotlib and strong exposure in regular expressions. 3+ years Hands on experience in Machine learning algorithms like SVM, CART, Bagging and Boosting algorithms, NLP based ML algorithms and Text mining. Hands on expertise to integrate multiple data sources in a streamlined pipeline.

What we are looking for : Apart from your love for data and ability to code even while sleeping you would need the following. Minimum of 3-8 years of experience in designing and delivery of data science solutions. You should have successful projects of retail/BFSI/FMCG/Manufacturing/QSR in your kitty to show-off. Deep understanding of various statistical techniques, mathematical models, and algorithms to start the conversation with the data in hand. Ability to choose the right model for the data and translate that into a code using R, Python, VBA, SQL, etc. What you will be doing : Understand business problems and translate business requirements into technical requirements. Conduct complex data analysis to ensure data quality & reliability i.e., make the data talk by extracting, preparing, and transforming it. Identify, develop and implement statistical techniques and algorithms to address business challenges and add value to the organization. Gather requirements and communicate findings in the form of a meaningful story with the stakeholders Build & implement data models using predictive modelling techniques . Interact with clients and provide support for queries and delivery adoption. Lead and mentor data analysts.

We are looking for 8+years experienced candidates for this role. Job Description A minimum of 8 years of professional experience, with at least 6 years in a data science role. Strong knowledge of statistical modeling, machine learning, deep learning and GenAI. Proficiency in Python and hands on experience optimizing code for performance. Experience with data preprocessing, feature engineering, data visualization and hyperparameter tuning. Solid understanding of database concepts and experience working with large datasets. Experience deploying and scaling machine learning models in a production environment. Familiarity with machine learning operations (MLOps) and related tools. Good understanding of Generative AI concepts and LLM finetuning. Excellent communication and collaboration skills. Responsibilities include: Lead a high performance team, guide and mentor them on the latest technology landscape, patterns and design standards and prepare them to take on new roles and responsibilities. Provide strategic direction and technical leadership for AI initiatives, guiding the team in designing and implementing state-of-the-art AI solutions. Lead the design and architecture of complex AI systems, ensuring scalability, reliability, and performance. Lead the development and deployment of machine learning/deep learning models to address key business challenges. Apply statistical modeling, data preprocessing, feature engineering, machine learning, and deep learning techniques to build and improve models. Utilize expertise in at least two of the following areas: computer vision, predictive analytics, natural language processing, time series analysis, recommendation systems. Design, implement, and optimize data pipelines for model training and deployment. Experience with model serving frameworks (e.g., TensorFlow Serving, TorchServe, KServe, or similar). Design and implement APIs for model serving and integration with other systems. Collaborate with cross-functional teams to define project requirements, develop solutions, and communicate results. Mentor junior data scientists, providing guidance on technical skills and project execution. Stay up-to-date with the latest advancements in data science and machine learning, particularly in generative AI, and evaluate their potential applications. Communicate complex technical concepts and analytical findings to both technical and non-technical audiences. Serves as a primary point of contact for client managers and liaises frequently with internal stakeholders to gather data or inputs needed for project work Certifications : Bachelor's or Master's degree in a quantitative field such as statistics, mathematics, computer science, or a related area. Primary Skills : Python Data Science concepts Pandas, NumPy, Matplotlib Artificial Intelligence Statistical Modeling Machine Learning, Natural Language Processing (NLP), Deep Learning Model Serving Frameworks (e.g., TensorFlow Serving, TorchServe) MLOps(e.g; MLflow, Tensorboard, Kubeflow etc) Computer Vision, Predictive Analytics, Time Series Analysis, Anomaly Detection, Recommendation Systems (Atleast 2) Generative AI, RAG, Finetuning(LoRa, QLoRa) Proficent in any of Cloud Computing Platforms (e.g., AWS, Azure, GCP) Secondary Skills : Expertise in designing scalable and efficient model architectures is crucial for developing robust AI solutions. Ability to assess and forecast the financial requirements of data science projects ensures alignment with budgetary constraints and organizational goals. Strong communication skills are vital for conveying complex technical concepts to both technical and non-technical stakeholders.

We are looking for 8+years experienced candidates for this role. Job Description A minimum of 8 years of professional experience, with at least 6 years in a data science role. Strong knowledge of statistical modeling, machine learning, deep learning and GenAI. Proficiency in Python and hands on experience optimizing code for performance. Experience with data preprocessing, feature engineering, data visualization and hyperparameter tuning. Solid understanding of database concepts and experience working with large datasets. Experience deploying and scaling machine learning models in a production environment. Familiarity with machine learning operations (MLOps) and related tools. Good understanding of Generative AI concepts and LLM finetuning. Excellent communication and collaboration skills. Responsibilities include: Lead a high performance team, guide and mentor them on the latest technology landscape, patterns and design standards and prepare them to take on new roles and responsibilities. Provide strategic direction and technical leadership for AI initiatives, guiding the team in designing and implementing state-of-the-art AI solutions. Lead the design and architecture of complex AI systems, ensuring scalability, reliability, and performance. Lead the development and deployment of machine learning/deep learning models to address key business challenges. Apply statistical modeling, data preprocessing, feature engineering, machine learning, and deep learning techniques to build and improve models. Utilize expertise in at least two of the following areas: computer vision, predictive analytics, natural language processing, time series analysis, recommendation systems. Design, implement, and optimize data pipelines for model training and deployment. Experience with model serving frameworks (e.g., TensorFlow Serving, TorchServe, KServe, or similar). Design and implement APIs for model serving and integration with other systems. Collaborate with cross-functional teams to define project requirements, develop solutions, and communicate results. Mentor junior data scientists, providing guidance on technical skills and project execution. Stay up-to-date with the latest advancements in data science and machine learning, particularly in generative AI, and evaluate their potential applications. Communicate complex technical concepts and analytical findings to both technical and non-technical audiences. Serves as a primary point of contact for client managers and liaises frequently with internal stakeholders to gather data or inputs needed for project work Certifications : Bachelor's or Master's degree in a quantitative field such as statistics, mathematics, computer science, or a related area. Primary Skills : Python Data Science concepts Pandas, NumPy, Matplotlib Artificial Intelligence Statistical Modeling Machine Learning, Natural Language Processing (NLP), Deep Learning Model Serving Frameworks (e.g., TensorFlow Serving, TorchServe) MLOps(e.g; MLflow, Tensorboard, Kubeflow etc) Computer Vision, Predictive Analytics, Time Series Analysis, Anomaly Detection, Recommendation Systems (Atleast 2) Generative AI, RAG, Finetuning(LoRa, QLoRa) Proficent in any of Cloud Computing Platforms (e.g., AWS, Azure, GCP) Secondary Skills : Expertise in designing scalable and efficient model architectures is crucial for developing robust AI solutions. Ability to assess and forecast the financial requirements of data science projects ensures alignment with budgetary constraints and organizational goals. Strong communication skills are vital for conveying complex technical concepts to both technical and non-technical stakeholders.

We are looking for 8+years experienced candidates for this role. Job Description A minimum of 8 years of professional experience, with at least 6 years in a data science role. Strong knowledge of statistical modeling, machine learning, deep learning and GenAI. Proficiency in Python and hands on experience optimizing code for performance. Experience with data preprocessing, feature engineering, data visualization and hyperparameter tuning. Solid understanding of database concepts and experience working with large datasets. Experience deploying and scaling machine learning models in a production environment. Familiarity with machine learning operations (MLOps) and related tools. Good understanding of Generative AI concepts and LLM finetuning. Excellent communication and collaboration skills. Responsibilities include: Lead a high performance team, guide and mentor them on the latest technology landscape, patterns and design standards and prepare them to take on new roles and responsibilities. Provide strategic direction and technical leadership for AI initiatives, guiding the team in designing and implementing state-of-the-art AI solutions. Lead the design and architecture of complex AI systems, ensuring scalability, reliability, and performance. Lead the development and deployment of machine learning/deep learning models to address key business challenges. Apply statistical modeling, data preprocessing, feature engineering, machine learning, and deep learning techniques to build and improve models. Utilize expertise in at least two of the following areas: computer vision, predictive analytics, natural language processing, time series analysis, recommendation systems. Design, implement, and optimize data pipelines for model training and deployment. Experience with model serving frameworks (e.g., TensorFlow Serving, TorchServe, KServe, or similar). Design and implement APIs for model serving and integration with other systems. Collaborate with cross-functional teams to define project requirements, develop solutions, and communicate results. Mentor junior data scientists, providing guidance on technical skills and project execution. Stay up-to-date with the latest advancements in data science and machine learning, particularly in generative AI, and evaluate their potential applications. Communicate complex technical concepts and analytical findings to both technical and non-technical audiences. Serves as a primary point of contact for client managers and liaises frequently with internal stakeholders to gather data or inputs needed for project work Certifications : Bachelor's or Master's degree in a quantitative field such as statistics, mathematics, computer science, or a related area. Primary Skills : Python Data Science concepts Pandas, NumPy, Matplotlib Artificial Intelligence Statistical Modeling Machine Learning, Natural Language Processing (NLP), Deep Learning Model Serving Frameworks (e.g., TensorFlow Serving, TorchServe) MLOps(e.g; MLflow, Tensorboard, Kubeflow etc) Computer Vision, Predictive Analytics, Time Series Analysis, Anomaly Detection, Recommendation Systems (Atleast 2) Generative AI, RAG, Finetuning(LoRa, QLoRa) Proficent in any of Cloud Computing Platforms (e.g., AWS, Azure, GCP) Secondary Skills : Expertise in designing scalable and efficient model architectures is crucial for developing robust AI solutions. Ability to assess and forecast the financial requirements of data science projects ensures alignment with budgetary constraints and organizational goals. Strong communication skills are vital for conveying complex technical concepts to both technical and non-technical stakeholders.

We are looking for 8+years experienced candidates for this role. Job Description A minimum of 8 years of professional experience, with at least 6 years in a data science role. Strong knowledge of statistical modeling, machine learning, deep learning and GenAI. Proficiency in Python and hands on experience optimizing code for performance. Experience with data preprocessing, feature engineering, data visualization and hyperparameter tuning. Solid understanding of database concepts and experience working with large datasets. Experience deploying and scaling machine learning models in a production environment. Familiarity with machine learning operations (MLOps) and related tools. Good understanding of Generative AI concepts and LLM finetuning. Excellent communication and collaboration skills. Responsibilities include: Lead a high performance team, guide and mentor them on the latest technology landscape, patterns and design standards and prepare them to take on new roles and responsibilities. Provide strategic direction and technical leadership for AI initiatives, guiding the team in designing and implementing state-of-the-art AI solutions. Lead the design and architecture of complex AI systems, ensuring scalability, reliability, and performance. Lead the development and deployment of machine learning/deep learning models to address key business challenges. Apply statistical modeling, data preprocessing, feature engineering, machine learning, and deep learning techniques to build and improve models. Utilize expertise in at least two of the following areas: computer vision, predictive analytics, natural language processing, time series analysis, recommendation systems. Design, implement, and optimize data pipelines for model training and deployment. Experience with model serving frameworks (e.g., TensorFlow Serving, TorchServe, KServe, or similar). Design and implement APIs for model serving and integration with other systems. Collaborate with cross-functional teams to define project requirements, develop solutions, and communicate results. Mentor junior data scientists, providing guidance on technical skills and project execution. Stay up-to-date with the latest advancements in data science and machine learning, particularly in generative AI, and evaluate their potential applications. Communicate complex technical concepts and analytical findings to both technical and non-technical audiences. Serves as a primary point of contact for client managers and liaises frequently with internal stakeholders to gather data or inputs needed for project work Certifications : Bachelor's or Master's degree in a quantitative field such as statistics, mathematics, computer science, or a related area. Primary Skills : Python Data Science concepts Pandas, NumPy, Matplotlib Artificial Intelligence Statistical Modeling Machine Learning, Natural Language Processing (NLP), Deep Learning Model Serving Frameworks (e.g., TensorFlow Serving, TorchServe) MLOps(e.g; MLflow, Tensorboard, Kubeflow etc) Computer Vision, Predictive Analytics, Time Series Analysis, Anomaly Detection, Recommendation Systems (Atleast 2) Generative AI, RAG, Finetuning(LoRa, QLoRa) Proficent in any of Cloud Computing Platforms (e.g., AWS, Azure, GCP) Secondary Skills : Expertise in designing scalable and efficient model architectures is crucial for developing robust AI solutions. Ability to assess and forecast the financial requirements of data science projects ensures alignment with budgetary constraints and organizational goals. Strong communication skills are vital for conveying complex technical concepts to both technical and non-technical stakeholders.

We are looking for 8+years experienced candidates for this role. Job Description A minimum of 8 years of professional experience, with at least 6 years in a data science role. Strong knowledge of statistical modeling, machine learning, deep learning and GenAI. Proficiency in Python and hands on experience optimizing code for performance. Experience with data preprocessing, feature engineering, data visualization and hyperparameter tuning. Solid understanding of database concepts and experience working with large datasets. Experience deploying and scaling machine learning models in a production environment. Familiarity with machine learning operations (MLOps) and related tools. Good understanding of Generative AI concepts and LLM finetuning. Excellent communication and collaboration skills. Responsibilities include: Lead a high performance team, guide and mentor them on the latest technology landscape, patterns and design standards and prepare them to take on new roles and responsibilities. Provide strategic direction and technical leadership for AI initiatives, guiding the team in designing and implementing state-of-the-art AI solutions. Lead the design and architecture of complex AI systems, ensuring scalability, reliability, and performance. Lead the development and deployment of machine learning/deep learning models to address key business challenges. Apply statistical modeling, data preprocessing, feature engineering, machine learning, and deep learning techniques to build and improve models. Utilize expertise in at least two of the following areas: computer vision, predictive analytics, natural language processing, time series analysis, recommendation systems. Design, implement, and optimize data pipelines for model training and deployment. Experience with model serving frameworks (e.g., TensorFlow Serving, TorchServe, KServe, or similar). Design and implement APIs for model serving and integration with other systems. Collaborate with cross-functional teams to define project requirements, develop solutions, and communicate results. Mentor junior data scientists, providing guidance on technical skills and project execution. Stay up-to-date with the latest advancements in data science and machine learning, particularly in generative AI, and evaluate their potential applications. Communicate complex technical concepts and analytical findings to both technical and non-technical audiences. Serves as a primary point of contact for client managers and liaises frequently with internal stakeholders to gather data or inputs needed for project work Certifications : Bachelor's or Master's degree in a quantitative field such as statistics, mathematics, computer science, or a related area. Primary Skills : Python Data Science concepts Pandas, NumPy, Matplotlib Artificial Intelligence Statistical Modeling Machine Learning, Natural Language Processing (NLP), Deep Learning Model Serving Frameworks (e.g., TensorFlow Serving, TorchServe) MLOps(e.g; MLflow, Tensorboard, Kubeflow etc) Computer Vision, Predictive Analytics, Time Series Analysis, Anomaly Detection, Recommendation Systems (Atleast 2) Generative AI, RAG, Finetuning(LoRa, QLoRa) Proficent in any of Cloud Computing Platforms (e.g., AWS, Azure, GCP) Secondary Skills : Expertise in designing scalable and efficient model architectures is crucial for developing robust AI solutions. Ability to assess and forecast the financial requirements of data science projects ensures alignment with budgetary constraints and organizational goals. Strong communication skills are vital for conveying complex technical concepts to both technical and non-technical stakeholders.

We are looking for 8+years experienced candidates for this role. Job Description A minimum of 8 years of professional experience, with at least 6 years in a data science role. Strong knowledge of statistical modeling, machine learning, deep learning and GenAI. Proficiency in Python and hands on experience optimizing code for performance. Experience with data preprocessing, feature engineering, data visualization and hyperparameter tuning. Solid understanding of database concepts and experience working with large datasets. Experience deploying and scaling machine learning models in a production environment. Familiarity with machine learning operations (MLOps) and related tools. Good understanding of Generative AI concepts and LLM finetuning. Excellent communication and collaboration skills. Responsibilities include: Lead a high performance team, guide and mentor them on the latest technology landscape, patterns and design standards and prepare them to take on new roles and responsibilities. Provide strategic direction and technical leadership for AI initiatives, guiding the team in designing and implementing state-of-the-art AI solutions. Lead the design and architecture of complex AI systems, ensuring scalability, reliability, and performance. Lead the development and deployment of machine learning/deep learning models to address key business challenges. Apply statistical modeling, data preprocessing, feature engineering, machine learning, and deep learning techniques to build and improve models. Utilize expertise in at least two of the following areas: computer vision, predictive analytics, natural language processing, time series analysis, recommendation systems. Design, implement, and optimize data pipelines for model training and deployment. Experience with model serving frameworks (e.g., TensorFlow Serving, TorchServe, KServe, or similar). Design and implement APIs for model serving and integration with other systems. Collaborate with cross-functional teams to define project requirements, develop solutions, and communicate results. Mentor junior data scientists, providing guidance on technical skills and project execution. Stay up-to-date with the latest advancements in data science and machine learning, particularly in generative AI, and evaluate their potential applications. Communicate complex technical concepts and analytical findings to both technical and non-technical audiences. Serves as a primary point of contact for client managers and liaises frequently with internal stakeholders to gather data or inputs needed for project work Certifications : Bachelor's or Master's degree in a quantitative field such as statistics, mathematics, computer science, or a related area. Primary Skills : Python Data Science concepts Pandas, NumPy, Matplotlib Artificial Intelligence Statistical Modeling Machine Learning, Natural Language Processing (NLP), Deep Learning Model Serving Frameworks (e.g., TensorFlow Serving, TorchServe) MLOps(e.g; MLflow, Tensorboard, Kubeflow etc) Computer Vision, Predictive Analytics, Time Series Analysis, Anomaly Detection, Recommendation Systems (Atleast 2) Generative AI, RAG, Finetuning(LoRa, QLoRa) Proficent in any of Cloud Computing Platforms (e.g., AWS, Azure, GCP) Secondary Skills : Expertise in designing scalable and efficient model architectures is crucial for developing robust AI solutions. Ability to assess and forecast the financial requirements of data science projects ensures alignment with budgetary constraints and organizational goals. Strong communication skills are vital for conveying complex technical concepts to both technical and non-technical stakeholders.

We are looking for 8+years experienced candidates for this role. Job Description A minimum of 8 years of professional experience, with at least 6 years in a data science role. Strong knowledge of statistical modeling, machine learning, deep learning and GenAI. Proficiency in Python and hands on experience optimizing code for performance. Experience with data preprocessing, feature engineering, data visualization and hyperparameter tuning. Solid understanding of database concepts and experience working with large datasets. Experience deploying and scaling machine learning models in a production environment. Familiarity with machine learning operations (MLOps) and related tools. Good understanding of Generative AI concepts and LLM finetuning. Excellent communication and collaboration skills. Responsibilities include: Lead a high performance team, guide and mentor them on the latest technology landscape, patterns and design standards and prepare them to take on new roles and responsibilities. Provide strategic direction and technical leadership for AI initiatives, guiding the team in designing and implementing state-of-the-art AI solutions. Lead the design and architecture of complex AI systems, ensuring scalability, reliability, and performance. Lead the development and deployment of machine learning/deep learning models to address key business challenges. Apply statistical modeling, data preprocessing, feature engineering, machine learning, and deep learning techniques to build and improve models. Utilize expertise in at least two of the following areas: computer vision, predictive analytics, natural language processing, time series analysis, recommendation systems. Design, implement, and optimize data pipelines for model training and deployment. Experience with model serving frameworks (e.g., TensorFlow Serving, TorchServe, KServe, or similar). Design and implement APIs for model serving and integration with other systems. Collaborate with cross-functional teams to define project requirements, develop solutions, and communicate results. Mentor junior data scientists, providing guidance on technical skills and project execution. Stay up-to-date with the latest advancements in data science and machine learning, particularly in generative AI, and evaluate their potential applications. Communicate complex technical concepts and analytical findings to both technical and non-technical audiences. Serves as a primary point of contact for client managers and liaises frequently with internal stakeholders to gather data or inputs needed for project work Certifications : Bachelor's or Master's degree in a quantitative field such as statistics, mathematics, computer science, or a related area. Primary Skills : Python Data Science concepts Pandas, NumPy, Matplotlib Artificial Intelligence Statistical Modeling Machine Learning, Natural Language Processing (NLP), Deep Learning Model Serving Frameworks (e.g., TensorFlow Serving, TorchServe) MLOps(e.g; MLflow, Tensorboard, Kubeflow etc) Computer Vision, Predictive Analytics, Time Series Analysis, Anomaly Detection, Recommendation Systems (Atleast 2) Generative AI, RAG, Finetuning(LoRa, QLoRa) Proficent in any of Cloud Computing Platforms (e.g., AWS, Azure, GCP) Secondary Skills : Expertise in designing scalable and efficient model architectures is crucial for developing robust AI solutions. Ability to assess and forecast the financial requirements of data science projects ensures alignment with budgetary constraints and organizational goals. Strong communication skills are vital for conveying complex technical concepts to both technical and non-technical stakeholders.

We are looking for 8+years experienced candidates for this role. Job Description A minimum of 8 years of professional experience, with at least 6 years in a data science role. Strong knowledge of statistical modeling, machine learning, deep learning and GenAI. Proficiency in Python and hands on experience optimizing code for performance. Experience with data preprocessing, feature engineering, data visualization and hyperparameter tuning. Solid understanding of database concepts and experience working with large datasets. Experience deploying and scaling machine learning models in a production environment. Familiarity with machine learning operations (MLOps) and related tools. Good understanding of Generative AI concepts and LLM finetuning. Excellent communication and collaboration skills. Responsibilities include: Lead a high performance team, guide and mentor them on the latest technology landscape, patterns and design standards and prepare them to take on new roles and responsibilities. Provide strategic direction and technical leadership for AI initiatives, guiding the team in designing and implementing state-of-the-art AI solutions. Lead the design and architecture of complex AI systems, ensuring scalability, reliability, and performance. Lead the development and deployment of machine learning/deep learning models to address key business challenges. Apply statistical modeling, data preprocessing, feature engineering, machine learning, and deep learning techniques to build and improve models. Utilize expertise in at least two of the following areas: computer vision, predictive analytics, natural language processing, time series analysis, recommendation systems. Design, implement, and optimize data pipelines for model training and deployment. Experience with model serving frameworks (e.g., TensorFlow Serving, TorchServe, KServe, or similar). Design and implement APIs for model serving and integration with other systems. Collaborate with cross-functional teams to define project requirements, develop solutions, and communicate results. Mentor junior data scientists, providing guidance on technical skills and project execution. Stay up-to-date with the latest advancements in data science and machine learning, particularly in generative AI, and evaluate their potential applications. Communicate complex technical concepts and analytical findings to both technical and non-technical audiences. Serves as a primary point of contact for client managers and liaises frequently with internal stakeholders to gather data or inputs needed for project work Certifications : Bachelor's or Master's degree in a quantitative field such as statistics, mathematics, computer science, or a related area. Primary Skills : Python Data Science concepts Pandas, NumPy, Matplotlib Artificial Intelligence Statistical Modeling Machine Learning, Natural Language Processing (NLP), Deep Learning Model Serving Frameworks (e.g., TensorFlow Serving, TorchServe) MLOps(e.g; MLflow, Tensorboard, Kubeflow etc) Computer Vision, Predictive Analytics, Time Series Analysis, Anomaly Detection, Recommendation Systems (Atleast 2) Generative AI, RAG, Finetuning(LoRa, QLoRa) Proficent in any of Cloud Computing Platforms (e.g., AWS, Azure, GCP) Secondary Skills : Expertise in designing scalable and efficient model architectures is crucial for developing robust AI solutions. Ability to assess and forecast the financial requirements of data science projects ensures alignment with budgetary constraints and organizational goals. Strong communication skills are vital for conveying complex technical concepts to both technical and non-technical stakeholders.