1345 Data Scientist Jobs - Page 49

Conduct cutting-edge research and develop advanced NLP algorithms and models. Build and fine-tune deep learning and machine learning models, with a focus on large language models. Work closely with internal stakeholders to define model requirements and ensure alignment with business objectives. Develop AI predictive models and perform data and model accuracy analyses. Produce and present findings, technical concepts, and model recommendations to both technical and non-technical stakeholders. Develop and maintain scripts/tools to automate both new model production and updates to existing model packages. Stay abreast of the latest advancements in data science research and contribute to the development of our knowledge base. Collaborate with developers to design automation and tool improvements for model building. Maintain documentation of processes and projects across all supported languages and environments. Have you got what it takes Masters degree in the field of Computer Science, Technology, Engineering, Math, or equivalent practical experience Minimum of 4-7 years of data science work experience, including implementing machine learning and NLP models using real-life data. Strong research skills, with a proven track record of developing and implementing advanced machine learning algorithms. Advanced knowledge of supervised and unsupervised machine learning algorithms. Excellent proficiency in Python programming. Experience with deep learning models and libraries such as PyTorch, TensorFlow, Hands-on experience with transformer models and Gen AI frameworks (HuggingFace, AWS Bedrock, Azure Foundry ). Strong verbal and written communication skills, including effective presentation abilities. Ability to work independently and as part of a team, demonstrating analytical thinking and problem-solving skills. You will have an advantage if you also have: Experience deploying models in production environments, ensuring scalability and performance using AWS/GCP/Azure Familiarity with relational databases and query languages (eg, MSSQL) and basic SQL knowledge. Experience with Retrieval-Augmented Generation (RAG) pipelines Understanding of multimodal models (text, audio, vision). Experience in Customer Experience domains. Experience working on international, globe-spanning teams. Past participation in a formal research setting. Experience as part of a software organization

As a Distinguished Data Scientist in the Catalog Data Science team, the candidate is expected to drive cutting edge innovation and business impact using AI, GenAI and broader data science capabilities. The candidate is also expected to demonstrate significant technical and thought leadership to elevate the catalog content quality. The Data Science and ML Engineering community at Walmart Global Tech is active in most of the Hack events, utilizing the petabytes of data at our disposal, to build some of the coolest ideas. All the work we'do at Walmart Global Tech will eventually benefit our operations our associates, helping Customers Save Money to Live Better. What you'll Do As a Distinguished Data Scientist, you'll have the opportunity to Formulating a strategy and roadmap to design, develop, and deploy AI/ML, NLP and GenAI models into production environments with a focus on reliability and scalability. Build/Fine-tune state-of-the-art large language models (LLMs) using Walmarts massive datasets. Lead and inspire a team of scientists and engineers solving AI/ML problems through RD while pushing the state-of-the-art to drive innovation at scale Executing full life cycle of projects through planning, data collection, model prototyping and deployment, with responsibilities encompassing stakeholder management and communication to cross-functional partners. Partner closely with Product and engineering leaders to inform, drive and accelerate innovations in discovery experiences via Insights, frameworks, machine learning prototypes, and the strategic importance of AI initiatives. Upholding standards, governance, and best practices in AI/ML model development and compliance with model and data governance standards. Build a strong external presence through publishing your team s work in top-tier AI/ML conferences and developing partnerships with academic institutions Adhere to Walmart s policies, procedures, mission, values, standards of ethics and integrity Adopt to Walmart s quality standards, develop/recommend process standards and best practices across the retail industry What you'll bring Bachelors/Masters/PhD from a reputed institution Minimum of 15+ years of data science experience Demonstrated history of technology leadership and strong hands-on experience Proven records of scientific publications or intellectual property generation Hands-on experience in Large Language Models, Multimodal Vision Language Models, Recommender Systems, Computer Vision, Optimization Models and Reinforcement Learning. Past experience in strong programming skills across data science, big data and ML engineering stack Strong communication skills with inclination to high ownership and commitment Good to haves: Experience with Ecommerce domain. Benefits Beyond our great compensation package, you can receive incentive awards for your performance. Other great perks include a host of best-in-class benefits maternity and parental leave, PTO, health benefits, and much more. Minimum Qualifications... Minimum Qualifications:Option 1: Bachelors degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 6 years experience in an analytics related field. Option 2: Masters degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 4 years experience in an analytics related field. Option 3: 8 years experience in an analytics or related field.

DAZN Group is looking for Data Scientist to join our dynamic team and embark on a rewarding career journey Undertaking data collection, preprocessing and analysis Building models to address business problems Presenting information using data visualization techniques 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 Build predictive models and machine-learning algorithms Combine models through ensemble modeling Present information using data visualization techniques Propose solutions and strategies to business challenges Collaborate with engineering and product development teams

Job Title: Senior / Lead Data Scientist India Locations: Bangalore, Chennai , Hyderabad Who we are Tiger Analytics is a global leader in AI and analytics, helping Fortune 1000 companies solve their toughest challenges. We offer full-stack AI and analytics services & solutions to empower businesses to achieve real outcomes and value at scale. We are on a mission to push the boundaries of what AI and analytics can do to help enterprises navigate uncertainty and move forward decisively. Our purpose is to provide certainty to shape a better tomorrow. Our team of 4000+ technologists and consultants are based in the US, Canada, the UK, India, Singapore and Australia, working closely with clients across CPG, Retail, Insurance, BFS, Manufacturing, Life Sciences, and Healthcare. Many of our team leaders rank in Top 10 and 40 Under 40 lists, exemplifying our dedication to innovation and excellence. We are a Great Place to Work-Certified (2022-24), recognized by analyst firms such as Forrester, Gartner, HFS, Everest, ISG and others. We have been ranked among the Best and Fastest Growing analytics firms lists by Inc. , Financial Times, Economic Times and Analytics India Magazine Curious about the role? What your typical day would look like? As a Senior Data Scientist, your work is a combination of hands-on contribution to Loreum Ipsum, Loreum Ipsum, etc. More specifically, this will involve: Lead and contribute to developing sophisticated machine learning models, predictive analytics, and statistical analyses to solve complex business problems. Demonstrate proficiency in programming languages such as Python or R, with the ability to write clean, efficient, and maintainable code. Experience with relevant libraries and frameworks (e. g. , TensorFlow, PyTorch, scikit-learn) is essential. Use your robust problem-solving skills to develop data-driven solutions, analyse complex datasets, and derive actionable insights that lead to impactful outcomes. Work closely with clients to understand their business objectives, identify opportunities for analytics-driven solutions, and communicate findings clearly and promptly. Take ownership of end-to-end model development, from problem definition and data exploration to model training, validation, and deployment. Collaborate with cross-functional teams, including data engineers, software developers, and business stakeholders, to integrate analytics solutions into business processes. Leverage a profound understanding of mathematical and statistical principles to guide developing and validating advanced data science models. Stay abreast of industry trends, emerging technologies, and best practices in data science, bringing innovative ideas to the team and contributing to continuous improvement. Desired Skills and Experience: 6-10 years of total DS and model development experience Mandatory : Minimum 3+ years of experience in the Banking and Financial services industry A passion for writing high-quality code (Python), and the code should be modular, scalable, and end-end project execution while planning an active hands-on role Having good problem-solving skills is essential, and it is equally important to have in-depth knowledge to solve complex problems effectively. Comprehensive knowledge of the regression and classification concepts and mathematical backend along with SQL Encourage collaboration with various stakeholders and take complete ownership of deliverables. Adept understanding of various data science approaches, machine learning algorithms, and statistical methods. Excellent communication skills with presentability, articulation, storytelling capability, and ability to manage complex client situations Effective mentoring of a team with expertise in industry/domain/functional areas. You are important to us, let s stay connected! Every individual comes with a different set of skills and qualities so even if you don t tick all the boxes for the role today, we urge you to apply as there might be a suitable/unique role for you tomorrow. We are an equal opportunity employer. Our diverse and inclusive culture and values guide us to listen, trust, respect, and encourage people to grow the way they desire. Note: The designation will be commensurate with expertise and experience. Compensation packages are among the best in the industry. Additional Benefits: Health insurance (self & family), virtual wellness platform, and knowledge communities

About the Opportunity : Ericsson is looking for a highly skilled Data Scientist with a minimum of 7 years of hands-on experience in Power BI, Tableau, Python, SQL, AI/ML, and Data Analytics . This role demands strong analytical thinking, data storytelling skills, and a deep understanding of machine learning models and data visualization techniques to drive strategic business decisions. What You will do : Design and develop interactive dashboards and reports using Power BI and Tableau . Build and deploy predictive models using Python and AI/ML frameworks . Perform advanced data analytics using SQL to derive actionable insights. Collaborate with cross-functional teams to define data requirements and deliver solutions. Translate complex datasets into strategic insights and compelling visual stories. Optimize data workflows and model performance for scalability and efficiency. The Skills you bring : Minimum 7 years of experience in data science and analytics. Strong proficiency in Power BI , Tableau , Python , and SQL . Proven track record in building and deploying AI/ML models . Solid understanding of statistical methods and data preprocessing techniques. Experience in telecom or related domains is a plus. Excellent communication and stakeholder management skills.

To facilitate the process of transparent and evidence informed decision making in the field of health, Government of India has created an institutional arrangement called the Health Technology Assessment in India (HTAIn) under the Department of Health Research (DHR). HTAIn is entrusted with the responsibility to collate and where needed generate evidence related to the clinical effectiveness, cost-effectiveness, and safety of medicines, devices and health programs using the Health Technology Assessment (HTA) approach. Indian Institute of Public Health, Hyderabad has been selected as a hub of HTAIn with the mandate of carrying out HTA for government and various other relevant agencies in that region. Qualification: Essential: PhD/Masters in Economics /Development Economics/Public Health with specialization in Health Economics, Health Financing and Health Policy. Desirable: Publication in reputed peer-reviewed journals will be given weightage Experience: Essential: Working post-degree in Health Economics research projects at middle to senior researcher level for 2-3 years. For PhD in Economics the post-PhD experience can be relaxed to 1 years provided the thesis was aligned to any public health project or programme and there are publication(s) from it Academic review (scoping and systematic) Competence at biostatistics/econometrics with fluent use of statistical software (preferably R and STATA) with working knowledge of large datasets.:

Job Description & Responsibilities 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 Build predictive models and machine-learning algorithms Combine models through ensemble modeling Present information using data visualization techniques Propose solutions and strategies to business challenges Collaborate with engineering and product development teams. Qualification, Skills & Experience Good hands-on experience in Advanced Python Programming Experiences in scalable Microservice Architecture and Development Good understanding of API Development, Messaging Queues and Asynchronous Task Management Basic DevOp skills and working with Docker Experience with LangChain, LangGraph, AutoGen or CrewAI are a big plus Ability to co-work in a small team with different locations Ability to learn and understand a new Python framework

Role & responsibilities Architect and implement Al solutions utilizing cutting-edge technologies like LLM, Langchain, and Machine Learning. AIML solution development in Azure using Python Ability to build and finetune the model to improve the performance Create own technology if off-the-shelf technology is not solving the problem. E.g changes to traditional RAG approaches, finetune LLM, create architectures. Lead from the front, responsible for coding, designing, and ensuring best practices & frameworks are adhered by the team. Create end to end AI systems with responsible AI principles Preferred candidate profile

Responsibilities : 1. Strategic Leadership : a. Define and drive the overall data science strategy and roadmap for the organization, aligning it with business objectives and technical capabilities. b. Oversee the design, development, and implementation of data science solutions. c. Foster a culture of innovation and continuous improvement within the data science team. 2. Data Strategy : a. Develop and deploy advanced data science models and algorithms, including LLMs, to solve complex business problems. Identify, acquire, and curate high-quality datasets relevant ML tasks. b. Design and implement data preprocessing, cleaning, and augmentation techniques. c. Leverage LLMs to extract deeper insights from data, including unstructured text and natural language data. 3. Data-Driven ML Development : a. Collaborate with LLM experts to integrate LLMs into data science pipelines and applications. b. Optimize LLM performance for specific tasks and domains. c. Apply advanced data mining and machine learning techniques to extract valuable insights. d. Evaluate ML performance using rigorous data-driven metrics. 4. ML Data Visualization and Analysis : a. Develop data visualizations and analysis techniques to understand ML Al behavior and performance. b. Identify trends, patterns, and anomalies in data. Explore new applications of LLMs in data science, such as LLM-powered recommendation systems, predictive analytics, and anomaly detection. c. Communicate data-driven insights to stakeholders effectively. Minimum Required Skills : - 11+ years of experience preferred. - Advanced degree in computer science, data science, or a related field. - Deep understanding of LLM architectures, algorithms, and techniques. - Strong experience in Python, SQL. - Should be extremely comfortable with Numpy, Pandas, Matplotlib and Scikit learn python libraries - Strong understanding of machine learning concepts and algorithms. Should know deep learning techniques such as clustering, decision trees, random forest, etc. - Knowledge on text classification, sentiment analysis, named entity recognition, machine translation, text summarization and question-answering is must. - Experience with LLM frameworks (Hugging Face Transformers, TensorFlow, PyTorch) - Experience with data labeling and annotation tools. - Certifications in cloud platforms or ML technologies can be a plus. - Proficient knowledge of cloud platforms (AWS, GCP, Azure). - Strong problem-solving and analytical skills. - Ability to work in team-oriented, collaborative environment. Keywords : - Data Scientist - Statistician - Data Engineer - Python - R - Supervised & Unsupervised learning - Machine Learning Algorithms - Deep Learning - Hugging Face - Natural Language Processing (NLP) - Computer Vision - TensorFlow - PyTorch - Scikit-learn - Transformers - LLM Frameworks - LLM Models - GPT -3, 4o - BERT - Llama

Role : Principal Data Scientist / LLM Specialist Responsibilities : 1. Strategic Leadership : a. Define and drive the overall data science strategy and roadmap for the organization, aligning it with business objectives and technical capabilities. b. Oversee the design, development, and implementation of data science solutions. c. Foster a culture of innovation and continuous improvement within the data science team. 2. Data Strategy : a. Develop and deploy advanced data science models and algorithms, including LLMs, to solve complex business problems. Identify, acquire, and curate high-quality datasets relevant ML tasks. b. Design and implement data preprocessing, cleaning, and augmentation techniques. c. Leverage LLMs to extract deeper insights from data, including unstructured text and natural language data. 3. Data-Driven ML Development : a. Collaborate with LLM experts to integrate LLMs into data science pipelines and applications. b. Optimize LLM performance for specific tasks and domains. c. Apply advanced data mining and machine learning techniques to extract valuable insights. d. Evaluate ML performance using rigorous data-driven metrics. 4. ML Data Visualization and Analysis : a. Develop data visualizations and analysis techniques to understand ML Al behavior and performance. b. Identify trends, patterns, and anomalies in data. Explore new applications of LLMs in data science, such as LLM-powered recommendation systems, predictive analytics, and anomaly detection. c. Communicate data-driven insights to stakeholders effectively. Minimum Required Skills : - 11+ years of experience preferred. - Advanced degree in computer science, data science, or a related field. - Deep understanding of LLM architectures, algorithms, and techniques. - Strong experience in Python, SQL. - Should be extremely comfortable with Numpy, Pandas, Matplotlib and Scikit learn python libraries - Strong understanding of machine learning concepts and algorithms. Should know deep learning techniques such as clustering, decision trees, random forest, etc. - Knowledge on text classification, sentiment analysis, named entity recognition, machine translation, text summarization and question-answering is must. - Experience with LLM frameworks (Hugging Face Transformers, TensorFlow, PyTorch) - Experience with data labeling and annotation tools. - Certifications in cloud platforms or ML technologies can be a plus. - Proficient knowledge of cloud platforms (AWS, GCP, Azure). - Strong problem-solving and analytical skills. - Ability to work in team-oriented, collaborative environment. Keywords : - Data Scientist - Statistician - Data Engineer - Python - R - Supervised & Unsupervised learning - Machine Learning Algorithms - Deep Learning - Hugging Face - Natural Language Processing (NLP) - Computer Vision - TensorFlow - PyTorch - Scikit-learn - Transformers - LLM Frameworks - LLM Models - GPT -3, 4o - BERT - Llama

As passionate about our people as we are about our mission. What We re All About : Q2 is proud of delivering our mobile banking platform and technology solutions, globally, to more than 22 million end users across our 1,300 financial institutions and fintech clients. At Q2, our mission is simple: Build strong, diverse communities by strengthening their financial institutions. We accomplish that by investing in the communities where both our customers and employees serve and live. What Makes Q2 Special? Being as passionate about our people as we are about our mission. We celebrate our employees in many ways, including our Circle of Awesomeness award ceremony and day of employee celebration among others! We invest in the growth and development of our team members through ongoing learning opportunities, mentorship programs, internal mobility, and meaningful leadership relationships. We also know that nothing builds trust and collaboration like having fun. We hold an annual Dodgeball for Charity event at our Q2 Stadium in Austin, inviting other local companies to play, and community organizations we support to raise money and awareness together. Q2 is seeking an Implementation Engineer who will Responsible for implementing Q2 s Ebanking Solutions in order to align with the business requirements of our customers. You will be exposed to a highly customizable product on multiple platforms that are configured/engineered differently for each customer. Must be exceptionally detail-oriented, an energetic self-starter who can work independently and in a group setting . This work is performed out of our Implementations Solution Center in Austin and does not require travel. RESPONSIBILITIES: Partner with clients and internal teams to understand business requirements and direct the configuration duties Develop and perform quality assurance check points within your team to ensure quality and timely delivery Take ownership of your team s business results by developing and leading training and execution plans Monitors and impacts key metrics and efficiencies Problem-solve routine to complex issues Establish strong working and strategic relationships to socialize initiatives and get buy-in across functions Provide Level 2 and 3 support to other team members Create and implement tools that increase quality, security and productivity Track status and provide updates in relation to overall implementation process Responsible for ensuring that all security, availability, confidentiality and privacy policies and controls are adhered to Work closely with Development and other teams to ensure client satisfaction and on-time delivery EXPERIENCE AND KNOWLEDGE: Bachelor s Degree in related field or equivalent experience Typically requires up to 2 years of related work experience Strong MS SQL skills: Understanding of DB Design and TSQL query language as related to Enterprise software configuration, installation and debugging Operating System, Hardware configuration and Network troubleshooting skills required with packet analysis valued Configuration and deployment experience with Web Services Some knowledge of HTML helpful Data migration experience a plus VMware experience valuable Experience with Python and other scripting languages Familiarity with iOS and Android mobile applications platforms helpful Strong troubleshooting, diagnostic and analytical skills. Attention to detail, exceptional follow-through, the ability to prioritize, stay organized, and multi-task in a fast-paced environment A relentlessly positive disposition Excellent people and teamwork skills with a drive for ownership of activities with a focus on successful completion. Ability to train individuals 1-on-1 and in a classroom environment The ability to remain calm, diplomatic, and cooperative under stressful conditions Strong written and oral communication skills including communication of technical concepts to non-technical individuals Enterprise Software experience Financial Services experience is beneficial but not a requirement This position requires fluent written and oral communication in English. Health & Wellness Hybrid Work Opportunities Flexible Time Off Career Development & Mentoring Programs Health & Wellness Benefits, including competitive health insurance offerings and generous paid parental leave for eligible new parents Community Volunteering & Company Philanthropy Programs Employee Peer Recognition Programs - You Earned it

Hiring for: A leading well funded B2B SaaS company serving global CPG clients in the supply chain domain. Part of one of the largest global Analytics consulting firms. Positions: 2 Location: Bangalore (Hybrid) Experience: Min. 6 years in DS, overall could be more Preferred Joining: Immediate to 30 days Reporting to: Director of Data Science Direct Reports: Zero (this is an IC role) Salary: 50L+ range based on fitment and skills Overview: As a Lead Data Scientist, you will be instrumental in shaping the company's next-generation AI-driven demand planning and optimization products. You will lead the design and deployment of data science solutions that power the company's core decision intelligence engine driving measurable business impact for our global clients. From problem scoping to model deployment, you will own the full data science lifecycle and work closely with cross-functional teams to integrate intelligence into key decision-making workflows. Role & Responsibilities: Conduct exploratory data analysis to uncover trends, patterns, and insights from complex datasets Design, train, and deploy machine learning and deep learning models for time series use cases such as demand forecasting, inventory management, and pricing Extract data insights, create visualizations, and communicate findings to technical and non-technical stakeholders Build and maintain data science pipelines for model development, deployment, monitoring, and updates Collaborate with engineering, product, and business teams to integrate models into production systems and align with client goals Research and prototype new algorithms and modelling techniques to improve solution performance Monitor and evaluate model performance and iterate based on finding Requirements: 6+ years of experience in data science, machine learning, or analytics roles Experience with time series analysis, forecasting, and predictive modelling. Proficient in Python (NumPy, pandas, Scikit-learn, TensorFlow, or PyTorch), SQL, and Excel Familiarity with deploying machine learning solutions and managing model lifecycle Ability to work with engineering and product teams to scope and deliver projects Ability to explain modelling choices, data assumptions, and outcomes to stakeholders Exposure to statistical methods, optimization, and model monitoring frameworks Prior experience working in CPG, FMCG, or retail industries is a plus

Blend is hiring a Senior Data Scientist (Generative AI) to spearhead the development of advanced AI-powered classification and matching systems on Databricks. You will contribute to flagship programs like the Diageo AI POC by building RAG pipelines, deploying agentic AI workflows, and scaling LLM-based solutions for high-precision entity matching and MDM modernization. Key Responsibilities Design and implement end-to-end AI pipelines for product classification, fuzzy matching, and deduplication using LLMs, RAG, and Databricks-native workflows . Develop scalable, reproducible AI solutions within Databricks notebooks and job clusters , leveraging Delta Lake, MLflow, and Unity Catalog. Engineer Retrieval-Augmented Generation (RAG) workflows using vector search and integrate with Python-based matching logic. Build agent-based automation pipelines (rule-driven + GenAI agents) for anomaly detection, compliance validation, and harmonization logic. Implement explainability, audit trails, and governance-first AI workflows aligned with enterprise-grade MDM needs. Collaborate with data engineers, BI teams, and product owners to integrate GenAI outputs into downstream systems. Contribute to modular system design and documentation for long-term scalability and maintainability. Bachelor s/Master s in Computer Science, Artificial Intelligence, or related field. 5+ years of overall Data Science experience with 2+ years in Generative AI / LLM-based applications. Deep experience with Databri

T&M Services Consulting Pvt. Ltd. is empaneled with Baroda Sun Technologies Limited (BSTL) for the recruitment of various positions. Baroda Sun Technologies Limited (BSTL) is a wholly owned subsidiary of Bank of Baroda, established with the approval of the Reserve Bank of India (RBI). It has been set up to provide IT services, drive digital transformation through new-age technologies, and develop innovative digital products and platforms for the Bank .BSTL is currently seeking to hire IT professionals on a contractual basis for its Mumbai office. Post Name: Data Scientist BASIC QUALIFICATION Essential: B.Tech / Master's in: Data Science Computer Science Statistics Applied Mathematics Or equivalent degree in the above-specified disciplines Minimum 50% score Degree must be from a University / Institution / Board recognized by the Government of India or approved by Government Regulatory Bodies OTHER QUALIFICATION (As on 31.03.2025) Preferred Certifications (Valid as on 31.03.2025) : Experience with cloud platforms such as: AWS Azure Google Cloud Exposure to big data technologies WORK EXPERIENCE (Post-Basic Qualification) Essential: Minimum 0 to 06 years post qualification experience in the IT Industry Preferred: Hands-on experience in relevant fields (within the essential experience period), especially in the BFSI sector Minimum 1 year of experience specifically as a Data Scientist Relevant Experience Areas: Programming Statistics and Probability Data Wrangling and Database Management Machine Learning and Deep Learning Data Visualization Cloud Computing Maximum Age: 40 years Interested candidates may submit application on the given website:- http://barodasuntechnologies.com/ Thanks & Regards T&M Services Consulting Pvt Ltd.

T&M Services Consulting Pvt. Ltd. is empaneled with Baroda Sun Technologies Limited (BSTL) for the recruitment of various positions. Baroda Sun Technologies Limited (BSTL) is a wholly owned subsidiary of Bank of Baroda, established with the approval of the Reserve Bank of India (RBI). It has been set up to provide IT services, drive digital transformation through new-age technologies, and develop innovative digital products and platforms for the Bank. BSTL is currently seeking to hire IT professionals on a contractual basis for its Mumbai office. Post Name: Data Scientist BASIC QUALIFICATION Essential: B.Tech / Master's in: Data Science Computer Science Statistics Applied Mathematics Or equivalent degree in the above-specified disciplines Minimum 50% score Degree must be from a University / Institution / Board recognized by the Government of India or approved by Government Regulatory Bodies OTHER QUALIFICATION (As on 31.03.2025) Preferred Certifications (Valid as on 31.03.2025) : Experience with cloud platforms such as: AWS Azure Google Cloud Exposure to big data technologies WORK EXPERIENCE (Post-Basic Qualification) Essential: Minimum 6 years post qualification experience in the IT Industry Preferred: Hands-on experience in relevant fields (within the essential experience period), especially in the BFSI sector Minimum 1 year of experience specifically as a Data Scientist Relevant Experience Areas: Programming Statistics and Probability Data Wrangling and Database Management Machine Learning and Deep Learning Data Visualization Cloud Computing Maximum Age: 40 years Interested candidates may submit application on the given website:- http://barodasuntechnologies.com/ Thanks & Regards T&M Services Consulting Pvt Ltd.

Role : Principal Data Scientist / LLM Specialist Responsibilities : Strategic Leadership :a. Define and drive the overall data science strategy and roadmap for the organization, aligning it with business objectives and technical capabilities.b. Oversee the design, development, and implementation of data science solutions.c. Foster a culture of innovation and continuous improvement within the data science team. Data Strategy :a. Develop and deploy advanced data science models and algorithms, including LLMs, to solve complex business problems. Identify, acquire, and curate high-quality datasets relevant ML tasks.b. Design and implement data preprocessing, cleaning, and augmentation techniques.c. Leverage LLMs to extract deeper insights from data, including unstructured text and natural language data. Data-Driven ML Development :a. Collaborate with LLM experts to integrate LLMs into data science pipelines and applications. b. Optimize LLM performance for specific tasks and domains.c. Apply advanced data mining and machine learning techniques to extract valuable insights.d. Evaluate ML performance using rigorous data-driven metrics. ML Data Visualization and Analysis :a. Develop data visualizations and analysis techniques to understand ML Al behavior and performance.b. Identify trends, patterns, and anomalies in data. Explore new applications of LLMs in data science, such as LLM-powered recommendation systems, predictive analytics, and anomaly detection.c. Communicate data-driven insights to stakeholders effectively. Minimum Required Skills :- 11+ years of experience preferred. - Advanced degree in computer science, data science, or a related field.- Deep understanding of LLM architectures, algorithms, and techniques.- Strong experience in Python, SQL. Should be extremely comfortable with Numpy, Pandas, Matplotlib and Scikit learn python libraries Strong understanding of machine learning concepts and algorithms. Should know deep learning techniques such as clustering, decision trees, random forest, etc. Knowledge on text classification, sentiment analysis, named entity recognition, machine translation, text summarization and question answering is must. Experience with LLM frameworks (Hugging Face Transformers, TensorFlow, PyTorch) Experience with data labeling and annotation tools. Certifications in cloud platforms or ML technologies can be a plus. Proficient knowledge of cloud platforms (AWS, GCP, Azure). Strong problem solving and analytical skills. Ability to work in team oriented, collaborative environment.Keywords : Data Scientist Statistician Data Engineer Python R Supervised & Unsupervised learning Machine Learning Algorithms Deep Learning Hugging Face Natural Language Processing (NLP) Computer Vision TensorFlow PyTorch Scikit learn Transformers LLM Frameworks LLM Models GPT 3, 4o BERT Llama

Responsibilities : 1. Strategic Leadership : a. Define and drive the overall data science strategy and roadmap for the organization, aligning it with business objectives and technical capabilities. b. Oversee the design, development, and implementation of data science solutions. c. Foster a culture of innovation and continuous improvement within the data science team. 2. Data Strategy : a. Develop and deploy advanced data science models and algorithms, including LLMs, to solve complex business problems. Identify, acquire, and curate high-quality datasets relevant ML tasks. b. Design and implement data preprocessing, cleaning, and augmentation techniques. c. Leverage LLMs to extract deeper insights from data, including unstructured text and natural language data. 3. Data-Driven ML Development : a. Collaborate with LLM experts to integrate LLMs into data science pipelines and applications. b. Optimize LLM performance for specific tasks and domains. c. Apply advanced data mining and machine learning techniques to extract valuable insights. d. Evaluate ML performance using rigorous data-driven metrics. 4. ML Data Visualization and Analysis : a. Develop data visualizations and analysis techniques to understand ML Al behavior and performance. b. Identify trends, patterns, and anomalies in data. Explore new applications of LLMs in data science, such as LLM-powered recommendation systems, predictive analytics, and anomaly detection. c. Communicate data-driven insights to stakeholders effectively. Minimum Required Skills : - 11+ years of experience preferred. - Advanced degree in computer science, data science, or a related field. - Deep understanding of LLM architectures, algorithms, and techniques. - Strong experience in Python, SQL. - Should be extremely comfortable with Numpy, Pandas, Matplotlib and Scikit learn python libraries - Strong understanding of machine learning concepts and algorithms. Should know deep learning techniques such as clustering, decision trees, random forest, etc. - Knowledge on text classification, sentiment analysis, named entity recognition, machine translation, text summarization and question-answering is must. - Experience with LLM frameworks (Hugging Face Transformers, TensorFlow, PyTorch) - Experience with data labeling and annotation tools. - Certifications in cloud platforms or ML technologies can be a plus. - Proficient knowledge of cloud platforms (AWS, GCP, Azure). - Strong problem-solving and analytical skills. - Ability to work in team-oriented, collaborative environment. Keywords : - Data Scientist - Statistician - Data Engineer - Python - R - Supervised & Unsupervised learning - Machine Learning Algorithms - Deep Learning - Hugging Face - Natural Language Processing (NLP) - Computer Vision - TensorFlow - PyTorch - Scikit-learn - Transformers - LLM Frameworks - LLM Models - GPT -3, 4o - BERT - Llama

Responsibilities : 1. Strategic Leadership : a. Define and drive the overall data science strategy and roadmap for the organization, aligning it with business objectives and technical capabilities. b. Oversee the design, development, and implementation of data science solutions. c. Foster a culture of innovation and continuous improvement within the data science team. 2. Data Strategy : a. Develop and deploy advanced data science models and algorithms, including LLMs, to solve complex business problems. Identify, acquire, and curate high-quality datasets relevant ML tasks. b. Design and implement data preprocessing, cleaning, and augmentation techniques. c. Leverage LLMs to extract deeper insights from data, including unstructured text and natural language data. 3. Data-Driven ML Development : a. Collaborate with LLM experts to integrate LLMs into data science pipelines and applications. b. Optimize LLM performance for specific tasks and domains. c. Apply advanced data mining and machine learning techniques to extract valuable insights. d. Evaluate ML performance using rigorous data-driven metrics. 4. ML Data Visualization and Analysis : a. Develop data visualizations and analysis techniques to understand ML Al behavior and performance. b. Identify trends, patterns, and anomalies in data. Explore new applications of LLMs in data science, such as LLM-powered recommendation systems, predictive analytics, and anomaly detection. c. Communicate data-driven insights to stakeholders effectively. Minimum Required Skills : - 11+ years of experience preferred. - Advanced degree in computer science, data science, or a related field. - Deep understanding of LLM architectures, algorithms, and techniques. - Strong experience in Python, SQL. - Should be extremely comfortable with Numpy, Pandas, Matplotlib and Scikit learn python libraries - Strong understanding of machine learning concepts and algorithms. Should know deep learning techniques such as clustering, decision trees, random forest, etc. - Knowledge on text classification, sentiment analysis, named entity recognition, machine translation, text summarization and question-answering is must. - Experience with LLM frameworks (Hugging Face Transformers, TensorFlow, PyTorch) - Experience with data labeling and annotation tools. - Certifications in cloud platforms or ML technologies can be a plus. - Proficient knowledge of cloud platforms (AWS, GCP, Azure). - Strong problem-solving and analytical skills. - Ability to work in team-oriented, collaborative environment. Keywords : - Data Scientist - Statistician - Data Engineer - Python - R - Supervised & Unsupervised learning - Machine Learning Algorithms - Deep Learning - Hugging Face - Natural Language Processing (NLP) - Computer Vision - TensorFlow - PyTorch - Scikit-learn - Transformers - LLM Frameworks - LLM Models - GPT -3, 4o - BERT - Llama

Required Skills & Qualifications: 3-5 years of hands-on experience in data science, machine learning, and statistical modeling. Strong expertise in time series forecasting (ARIMA, XGBoost, RandomForest, TFT, NHITS, etc.) and familiarity with deep learning frameworks (TensorFlow, PyTorch). Excellent programming skills in Python (preferred), with proficiency in libraries such as NumPy, Pandas, scikit-learn, and visualization tools (Matplotlib, Seaborn, Plotly). Solid conceptual understanding of machine learning algorithms, deep learning architectures, and statistical methods. Experience with data preprocessing, feature engineering, and model evaluation. Ability to learn quickly and adapt to new technologies, tools, and methodologies. Strong problem-solving skills and a keen attention to detail. Excellent communication and presentation skills. Preferred Qualifications: Experience with cloud platforms and MLOps tools. Exposure to big data technologies (Spark, Hadoop) is a plus. Masters degree in Computer Science, Statistics, Mathematics, or a related field.

Role : Principal Data Scientist / LLM Specialist Responsibilities : 1. Strategic Leadership : a. Define and drive the overall data science strategy and roadmap for the organization, aligning it with business objectives and technical capabilities. b. Oversee the design, development, and implementation of data science solutions. c. Foster a culture of innovation and continuous improvement within the data science team. 2. Data Strategy : a. Develop and deploy advanced data science models and algorithms, including LLMs, to solve complex business problems. Identify, acquire, and curate high-quality datasets relevant ML tasks. b. Design and implement data preprocessing, cleaning, and augmentation techniques. c. Leverage LLMs to extract deeper insights from data, including unstructured text and natural language data. 3. Data-Driven ML Development : a. Collaborate with LLM experts to integrate LLMs into data science pipelines and applications. b. Optimize LLM performance for specific tasks and domains. c. Apply advanced data mining and machine learning techniques to extract valuable insights. d. Evaluate ML performance using rigorous data-driven metrics. 4. ML Data Visualization and Analysis : a. Develop data visualizations and analysis techniques to understand ML Al behavior and performance. b. Identify trends, patterns, and anomalies in data. Explore new applications of LLMs in data science, such as LLM-powered recommendation systems, predictive analytics, and anomaly detection. c. Communicate data-driven insights to stakeholders effectively. Minimum Required Skills : - 11+ years of experience preferred. - Advanced degree in computer science, data science, or a related field. - Deep understanding of LLM architectures, algorithms, and techniques. - Strong experience in Python, SQL. - Should be extremely comfortable with Numpy, Pandas, Matplotlib and Scikit learn python libraries - Strong understanding of machine learning concepts and algorithms. Should know deep learning techniques such as clustering, decision trees, random forest, etc. - Knowledge on text classification, sentiment analysis, named entity recognition, machine translation, text summarization and question-answering is must. - Experience with LLM frameworks (Hugging Face Transformers, TensorFlow, PyTorch) - Experience with data labeling and annotation tools. - Certifications in cloud platforms or ML technologies can be a plus. - Proficient knowledge of cloud platforms (AWS, GCP, Azure). - Strong problem-solving and analytical skills. - Ability to work in team-oriented, collaborative environment. Keywords : - Data Scientist - Statistician - Data Engineer - Python - R - Supervised & Unsupervised learning - Machine Learning Algorithms - Deep Learning - Hugging Face - Natural Language Processing (NLP) - Computer Vision - TensorFlow - PyTorch - Scikit-learn - Transformers - LLM Frameworks - LLM Models - GPT -3, 4o - BERT - Llama

: Role : Principal Data Scientist / LLM Specialist Responsibilities : 1. Strategic Leadership : a. Define and drive the overall data science strategy and roadmap for the organization, aligning it with business objectives and technical capabilities. b. Oversee the design, development, and implementation of data science solutions. c. Foster a culture of innovation and continuous improvement within the data science team. 2. Data Strategy : a. Develop and deploy advanced data science models and algorithms, including LLMs, to solve complex business problems. Identify, acquire, and curate high-quality datasets relevant ML tasks. b. Design and implement data preprocessing, cleaning, and augmentation techniques. c. Leverage LLMs to extract deeper insights from data, including unstructured text and natural language data. 3. Data-Driven ML Development : a. Collaborate with LLM experts to integrate LLMs into data science pipelines and applications. b. Optimize LLM performance for specific tasks and domains. c. Apply advanced data mining and machine learning techniques to extract valuable insights. d. Evaluate ML performance using rigorous data-driven metrics. 4. ML Data Visualization and Analysis : a. Develop data visualizations and analysis techniques to understand ML Al behavior and performance. b. Identify trends, patterns, and anomalies in data. Explore new applications of LLMs in data science, such as LLM-powered recommendation systems, predictive analytics, and anomaly detection. c. Communicate data-driven insights to stakeholders effectively. Minimum Required Skills : - 11+ years of experience preferred. - Advanced degree in computer science, data science, or a related field. - Deep understanding of LLM architectures, algorithms, and techniques. - Strong experience in Python, SQL. - Should be extremely comfortable with Numpy, Pandas, Matplotlib and Scikit learn python libraries - Strong understanding of machine learning concepts and algorithms. Should know deep learning techniques such as clustering, decision trees, random forest, etc. - Knowledge on text classification, sentiment analysis, named entity recognition, machine translation, text summarization and question-answering is must. - Experience with LLM frameworks (Hugging Face Transformers, TensorFlow, PyTorch) - Experience with data labeling and annotation tools. - Certifications in cloud platforms or ML technologies can be a plus. - Proficient knowledge of cloud platforms (AWS, GCP, Azure). - Strong problem-solving and analytical skills. - Ability to work in team-oriented, collaborative environment. Keywords : - Data Scientist - Statistician - Data Engineer - Python - R - Supervised & Unsupervised learning - Machine Learning Algorithms - Deep Learning - Hugging Face - Natural Language Processing (NLP) - Computer Vision - TensorFlow - PyTorch - Scikit-learn - Transformers - LLM Frameworks - LLM Models - GPT -3, 4o - BERT - Llama

You'll be Responsible for: Design, develop and implement cutting-edge AI/ML solutions, including Large Language Models (LLMs) and Generative AI applications Lead projects end-to-end while mentoring team members in AI-ML, including traditional ML and emerging AI technologies Drive innovation in AI agent development and orchestration for automated decision-making systems Establish best practices for responsible AI development and deployment What you'd have: AI-ML Engineer or Data Scientist with 3 11 years of relevant experience Strong expertise in modern AI frameworks and tools: ML/DL frameworks (TensorFlow, PyTorch, Keras, Sklearn) LLM frameworks (LangChain, LlamaIndex, CrewAI, AutoGen) Vector databases (Pinecone, Weaviate, ChromaDB) – Good To Have Hands-on experience with: Generative AI and foundation models Prompt engineering and LLM fine-tuning AI agent development and orchestration RAG (Retrieval-Augmented Generation) systems Proven experience in data preparation, including: Advanced data preprocessing techniques Feature engineering Data quality assessment and improvement Proficiency in data exploration tools (Pandas, Numpy, Polars) Strong programming skills in Python; R is a plus Deep understanding of: Statistics and probability ML/DL algorithms AI governance and responsible AI practices Experience with: Large-scale data processing Model deployment and MLOps Cost optimization for AI systems Track record of 3-5 successful AI/ML projects in production Excellent communication skills and team leadership ability Continuous learning mindset for emerging AI technologies Skills: Statistics and Mathematics Classical Machine Learning Deep Learning and Neural Networks Generative AI and LLMs Agentic AI Development MLOps and Production Engineering Data Engineering Model Optimization and Tuning AI Governance and Ethics Team Leadership Why join us? Impactful Work: Drive innovation in AI technologies while safeguarding Tanla's assets, data, and reputation Growth Opportunities: Be part of a rapidly growing company in the telecom and CPaaS space, with clear paths for professional advancement Innovative Environment: Work with a world-class team on cutting-edge AI technologies in a challenging and collaborative environment Research Opportunities: Contribute to the advancement of GenAI and Agentic AI technologies Tanla is an equal opportunity employer. We champion diversity and are committed to creating an inclusive environment for all employees. www.tanla.com

Role: Gen AI Engineer Experience: 8yr to 15 yr Location: PAN India Job Description: Collect and prepare data for training and evaluating multimodal foundation models. This may involve cleaning and processing text data or creating synthetic data. Develop and optimize large-scale language models like GANs (Generative Adversarial Networks) and VAEs (Variational Autoencoders) Work on tasks involving language modeling, text generation, understanding, and contextual comprehension. Regularly review and fine-tune Large Language models to ensure maximum accuracy and relevance for custom datasets. Build and deploy AI applications on cloud platforms any hyperscaler Azure, GCP or AWS. Integrate AI models with our company's data to enhance and augment existing applications. Role & Responsibility Handle data preprocessing, augmentation, and generation of synthetic data. Design and develop backend services using Python or .NET to support OpenAI-powered solutions (or any other LLM solution) Develop and Maintaining AI Pipelines Work with custom datasets, utilizing techniques like chunking and embeddings, to train and fine-tune models. Integrate Azure cognitive services (or equivalent platform services) to extend functionality and improve AI solutions Collaborate with cross-functional teams to ensure smooth deployment and integration of AI solutions. Ensure the robustness, efficiency, and scalability of AI systems. Stay updated with the latest advancements in AI and machine learning technologies. Skills & Experience Strong foundation in machine learning, deep learning, and computer science. Expertise in generative AI models and techniques (e.g., GANs, VAEs, Transformers). Experience with natural language processing (NLP) and computer vision is a plus. Ability to work independently and as part of a team. Knowledge of advanced programming like Python, and especially AI-centric libraries like TensorFlow, PyTorch, and Keras. This includes the ability to implement and manipulate complex algorithms fundamental to developing generative AI models. Knowledge of Natural language processing (NLP) for text generation projects like text parsing, sentiment analysis, and the use of transformers like GPT (generative pre-trained transformer) models. Experience in Data management, including data pre-processing, augmentation, and generation of synthetic data. This involves cleaning, labeling, and augmenting data to train and improve AI models. Experience in developing and deploying AI models in production environments. Knowledge of cloud services (AWS, Azure, GCP) and understanding of containerization technologies like Docker and orchestration tools like Kubernetes for deploying , managing and scaling AI solutions Should be able to bring new ideas and innovative solutions to our clients

Responsibilities : 1. Strategic Leadership : a. Define and drive the overall data science strategy and roadmap for the organization, aligning it with business objectives and technical capabilities. b. Oversee the design, development, and implementation of data science solutions. c. Foster a culture of innovation and continuous improvement within the data science team. 2. Data Strategy : a. Develop and deploy advanced data science models and algorithms, including LLMs, to solve complex business problems. Identify, acquire, and curate high-quality datasets relevant ML tasks. b. Design and implement data preprocessing, cleaning, and augmentation techniques. c. Leverage LLMs to extract deeper insights from data, including unstructured text and natural language data. 3. Data-Driven ML Development : a. Collaborate with LLM experts to integrate LLMs into data science pipelines and applications. b. Optimize LLM performance for specific tasks and domains. c. Apply advanced data mining and machine learning techniques to extract valuable insights. d. Evaluate ML performance using rigorous data-driven metrics. 4. ML Data Visualization and Analysis : a. Develop data visualizations and analysis techniques to understand ML Al behavior and performance. b. Identify trends, patterns, and anomalies in data. Explore new applications of LLMs in data science, such as LLM-powered recommendation systems, predictive analytics, and anomaly detection. c. Communicate data-driven insights to stakeholders effectively. Minimum Required Skills : - 11+ years of experience preferred. - Advanced degree in computer science, data science, or a related field. - Deep understanding of LLM architectures, algorithms, and techniques. - Strong experience in Python, SQL. - Should be extremely comfortable with Numpy, Pandas, Matplotlib and Scikit learn python libraries - Strong understanding of machine learning concepts and algorithms. Should know deep learning techniques such as clustering, decision trees, random forest, etc. - Knowledge on text classification, sentiment analysis, named entity recognition, machine translation, text summarization and question-answering is must. - Experience with LLM frameworks (Hugging Face Transformers, TensorFlow, PyTorch) - Experience with data labeling and annotation tools. - Certifications in cloud platforms or ML technologies can be a plus. - Proficient knowledge of cloud platforms (AWS, GCP, Azure). - Strong problem-solving and analytical skills. - Ability to work in team-oriented, collaborative environment. Keywords : - Data Scientist - Statistician - Data Engineer - Python - R - Supervised & Unsupervised learning - Machine Learning Algorithms - Deep Learning - Hugging Face - Natural Language Processing (NLP) - Computer Vision - TensorFlow - PyTorch - Scikit-learn - Transformers - LLM Frameworks - LLM Models - GPT -3, 4o - BERT - Llama.

Role & responsibilities esponsibilities 1Design develop test and implement AI and ML models using the latest technologies and frameworks 2Analyze and interpret complex data to identify trends patterns and insights 3Work with AI lead to understand business objectives and requirements and develop solutions to solve complex problems 4Maintain uptodate knowledge of latest AIML trends techniques and technologies 5Collaborate with data engineers to build data and model pipelines 6Conduct research and implement new methodologies in AI and ML ESSENTIAL SKILLS COMPETENCIES Minimum 5to 6 years of experience in implementing AI and ML models Excellent problemsolving skills with the ability to work independently as well as collaboratively in a team Solid understanding of machine learning algorithms and principles and their applicability to different problems Proficiency in Python and familiarity with libraries like TensorFlow Keras PyTorch or similar ML libraries Experience with GenAI would be highly beneficial Strong communication and presentation skills Skills Mandatory Skills : Prompt Engineering & RAG Good to Have Skills : Fine Tuning Large Language Models Preferred candidate profile