26 Predictive Modelling Jobs

As a Decision Science Specialist within the Accenture Strategy & Consulting Global Network Data & AI team, specializing in the Insurance practice, you will play a crucial role in helping our clients revolutionize their business operations. From conceptualization to implementation, you will collaborate with Property & Casualty insurers, Life & Retirement insurers, reinsurers, and brokers throughout the value chain. Your primary focus will be on enhancing analytic capabilities, ranging from data access and reporting to predictive modeling and Generative AI, to ensure that our clients stay ahead of the competition. The Accenture Global Network is a dynamic environment that seamlessly integrates Strategy & Consulting with Data and Artificial Intelligence, driving innovation and growth. You will have the opportunity to be part of a diverse and global community that continuously pushes the boundaries of business capabilities. Accenture's commitment to individual development and growth is unwavering, providing you with a supportive environment for learning and advancement. In this role, your responsibilities will include collaborating with the team to design, develop, deploy, and monitor advanced analytics models, leveraging cutting-edge technologies such as Generative AI. You will be instrumental in building functional aspects of Generative AI pipelines, optimizing system performance, and ensuring seamless data retrieval and storage. Additionally, you will engage with clients and account teams to identify engineering and business challenges, translating them into actionable analytics problems that drive operational enhancements and strategic insights. Your ability to synthesize data from diverse sources and present actionable insights in a clear and concise manner will be pivotal in facilitating informed decision-making for both technical and non-technical stakeholders. By harnessing your expertise in AI/ML tools and techniques, coupled with strong domain knowledge in the insurance sector, you will contribute significantly to delivering exceptional value to our clients. Join us on this exciting journey at Accenture, where you will be at the forefront of driving innovation, shaping the future of business, and making a tangible impact on our clients" success.,

Are you ready to disrupt an industry and change lives As an Associate at GCC's Sampling Allocation Service in AstraZeneca, you will be responsible for developing and implementing analytical programs to optimize sampling distributions for branded products. This role is a blend of managerial and hands-on tasks, involving proactive collaboration with brand team members and overseeing the internal GCC Sampling team to ensure deliverables meet specific requirements. Your role will require working closely with brand teams to comprehend rules, requirements, and sampling strategies, utilizing your expertise across various commercial datasets to ensure accurate implementation. Your contributions will play a vital role in the sample ordering and distribution system, directly influencing the development of life-changing medicines. Location: Bangalore Experience: 3-6 years Notice period: Maximum 2 months (strictly) **Essential Skills/Experience:** - A quantitative Bachelor's degree from an accredited institution in fields like Engineering, Operations Research, Management Science, Economics, Statistics, Applied Math, Computer Science, or Data Science is mandatory. An advanced degree (Masters, MBA, or PhD) is preferred. - Minimum of 2 years of experience in Pharmaceutical/Biotech/Healthcare analytics or secondary data analysis. - At least 3 years of experience in applying advanced methods and statistical procedures on large and disparate datasets, with expertise in areas such as Data Mining, Predictive Modeling algorithms, Optimisation & Simulation. - Proficiency and recent experience (2+ years) in Python, R, SQL, and big data technologies. - Working knowledge of data visualization tools like PowerBI, VBA, or similar platforms. - Proficiency in MS Office products, including PowerApps, Excel, and PowerPoint. - Ability to manipulate and extract insights from extensive longitudinal data sources like Claims, EMR, and other patient-level datasets. - Expertise in managing and analyzing various large, secondary transactional databases. - Background in statistical analysis and modeling, with Machine Learning knowledge as a plus. - Familiarity with IQVIA datasets and sales-related data sets like targeting and alignment, HCP eligibility, and call data. - Experience in data visualization methods and tools for effective communication of insights derived from analyses. - Strong organization and time management skills. **Desirable Skills/Experience:** - Strong leadership and interpersonal skills, with a proven ability to collaborate effectively with business leaders and cross-functional partners. - Excellent communication and influencing abilities, capable of presenting concise and compelling reviews of independently developed analyses along with actionable insights to stakeholders. - Strategic and critical thinking skills, with the capability to engage, build credibility, and maintain relationships with the Commercial Leadership Team. - Exceptional organizational skills and time management, adept at handling multiple projects simultaneously.,

As a Decision Science Specialist with Accenture Strategy & Consulting, Global Network Data & AI Practice focusing on Insurance, you will play a crucial role in helping clients transform their businesses through advanced analytics models, including Generative AI. You will collaborate with the team to architect, design, build, deploy, deliver, and monitor these models to address various client challenges effectively. Your responsibilities will include developing the functional aspects of Generative AI pipelines, implementing information retrieval and storage techniques, and optimizing systems across cloud platforms like Azure or AWS. You will engage with clients and account teams to comprehend engineering and business issues, translating them into analytics problems that provide actionable insights and operational enhancements. Furthermore, you will be tasked with extracting data from multiple sources and presenting relevant information in a clear and concise manner. Your ability to deliver valuable insights to both technical and non-technical audiences will be instrumental in driving business impact and fostering strategic decision-making. Joining Accenture's Global Network offers you the opportunity to be part of a dynamic and diverse community that continuously pushes the boundaries of business capabilities. With a focus on learning and growth, Accenture is committed to providing a stimulating work environment where you can thrive professionally. Additionally, being ranked 10th on the 2023 World's Best Workplaces list underscores Accenture's reputation as an excellent employer, making it an ideal place for you to advance your career.,

Be part of the future HR transformation at the dynamic intersection of people strategy, technology, and data-driven insights! We're seeking a leader to modernize and optimize our HR digital landscape across our global operations. This is your opportunity to architect extraordinary employee experiences, drive enterprise-wide innovation, and deliver measurable business value through strategic HR digital solutions and advanced analytics. As the Head of HR Digital Enablement & Analytics, you'll develop comprehensive strategies that support our HR solution vision while leading our talented People Analytics team. You'll serve as a key strategic partner to the HR Executive Team, deeply understanding our global HR organization's needs and collaborating with Group Digital & Technology to transform these insights into innovative digital solutions that enhance efficiency, effectiveness, and employee experience across the organization. Collaborate with HR teams, Group Digital & Technology, and key stakeholders to define and champion long-term HR process, employee experience, and solution strategies that enable Swiss Re's business objectives. Lead the People Analytics team in developing comprehensive analytics strategies, building predictive models, and creating advanced reporting capabilities that drive organizational insights and strategic decision-making. Drive partnerships between HR COEs and Group Digital and Technology to optimize HR processes through service design and strategic technology implementation, identifying emerging HR technologies that enhance employee experience. Understand HR needs and spearhead digital transformation initiatives across the HR function with significant business impact, working with users to evaluate service efficacy and recommend improvements. Partner with Group Digital & Technology to facilitate a portfolio of transformation initiatives, ensuring value-driven investment decisions and developing metrics to gauge HR process effectiveness. Collaborate with technical teams to create frameworks ensuring data integrity, accessibility, and compliance across HR systems while mitigating risks associated with HR processes. Cultivate relationships with key external partners to influence roadmaps and integrate innovative solutions into HR processes. You and your team will be part of the HR Operational Excellence function, a global, cross-functional group dedicated to enhancing the performance, efficiency, and impact of HR services across the organization. The HR Digital and Analytics team that you will lead plays a central role in enabling strategic HR transformation. The team drives continuous improvement across HR services, processes, and systems, and promotes data-driven decision-making by fostering learning through innovative programs like #iLearn and facilitating global collaboration through community dashboards. You're an experienced leader who thrives at the intersection of people strategy, HR service design, digital innovation, and workforce analytics. Your consultative approach allows you to translate complex business challenges into transformative digital solutions. You possess exceptional influencing skills that enable you to navigate organizational complexity and build consensus among diverse stakeholders. Your forward-thinking strategic mindset is balanced by pragmatic execution capabilities and a genuine passion for creating technology and data solutions that enhance workplace experiences. University degree and/or equivalent professional qualification in a related field. Minimum 10 years of significant track record in similar role(s) acquiring relevant skills in HR transformation, service design, technology-enabled transformation, and data analytics. Deep knowledge and experience in global HR business processes, including strategy development, service delivery, human capital management technologies, with the ability to translate business needs into technology requirements. Advanced expertise in people analytics, data visualization, statistical analysis, and predictive modeling for workforce insights, with experience leading HR data analytics teams and building capabilities within HR functions. Experience working with enterprise HRIS platforms (Workday, SAP SuccessFactors, Oracle HCM). Proficiency with data analytics tools and languages (Power BI, Tableau, R, Python, SQL). Demonstrated ability to influence, collaborate, and manage change with key stakeholders across global, matrix organizations. Knowledge of emerging technologies including GenAI and their application to HR. Executive education in digital transformation or advanced HR technology certifications (HRIP, SHRM-SCP). Strategic vendor management experience. Our company has a hybrid work model where the expectation is that you will be in the office three days per week. This role is not eligible for either relocation assistance or visa sponsorship. Swiss Re is one of the world's leading providers of reinsurance, insurance, and other forms of insurance-based risk transfer, working to make the world more resilient. We anticipate and manage a wide variety of risks, from natural catastrophes and climate change to cybercrime. We cover both Property & Casualty and Life & Health. Combining experience with creative thinking and cutting-edge expertise, we create new opportunities and solutions for our clients. This is possible thanks to the collaboration of more than 14,000 employees across the world.,

The ideal candidate's favourite words are learning, data, scale, and agility. You will leverage your strong collaboration skills and ability to extract valuable insights from highly complex data sets to ask the right questions and find the correct answers. Responsibilities Analyze raw data: assessing quality, cleansing, and structuring for downstream processing. Design accurate and scalable prediction algorithms. Molecular Docking and Simulation. Integrating Biological Data. Computational Biology related works. Qualifications Bachelor's degree or equivalent experience in a quantitative field (Bio-informatics, Biotechnology, Statistics, Computer Science, Engineering, etc.) At least 1 - 2 years of experience in quantitative analytics or data modelling Freshers can also apply.* Deep understanding of predictive modelling, machine learning, clustering and classification techniques, and algorithms Fluency in a programming language (Python, R, C, C++, Java, SQL),

As a Director of Machine Learning Engineering within Mastercard's Business & Market Insights (B&MI) group, you will play a crucial role in executing the AI/ML strategy for the Operational Insights Program. Your responsibilities will involve collaborating with internal and external partners to drive business growth, enhance customer experience, and ensure the delivery of secure, scalable, and high-performing software solutions. In this leadership position, you will be responsible for overseeing the design, development, and deployment of machine learning models and systems. Your expertise will be instrumental in providing valuable insights and guidance on technology approach and processes, contributing to strategic vision, and staying updated on the latest advancements in machine learning and AI technologies. Moreover, you will work closely with business partners on product definition, engage in vendor management, ensure regulatory compliance, and drive scalability, security, and performance across all software solutions and platforms. Your role will also involve fostering a culture of innovation, collaboration, and continuous learning within the team, while attracting, hiring, and developing top engineering talent. To excel in this position, you should hold a Masters/Bachelor's degree in computer science or engineering, with a proven track record of successfully leading and managing complex projects/products. Strong analytical and problem-solving abilities, along with hands-on experience in advanced statistical techniques, predictive modeling, and deep learning frameworks are essential. Proficiency in programming languages such as Java/Python/SQL, familiarity with data visualization tools, and cloud computing services will be advantageous. Your ability to communicate effectively, engage with stakeholders at all levels, and lead diverse global teams will be critical. Additionally, your commitment to responsible AI practices and information security will be paramount. If you are a detail-oriented, proactive leader with a passion for driving innovation and delivering excellence, we invite you to join our team and contribute to our mission of empowering organizations through data-driven insights and advanced analytics.,

As a seasoned Data Analyst with over 10 years of experience, you will play a crucial role in the development and implementation of data analytics strategies, frameworks, and methodologies that are in line with the goals and objectives of the organization. Your primary responsibility will be to drive the identification and exploration of data-driven opportunities to optimize business performance, enhance operational efficiency, and achieve strategic objectives. You will collaborate closely with senior leaders and stakeholders to define analytical requirements, establish key performance indicators (KPIs), and develop metrics to measure business performance and progress. Additionally, you will design and implement advanced analytical models and algorithms to extract insights, uncover patterns, and make predictions using large and complex data sets. Your expertise in data analysis, statistical modeling, and machine learning techniques will be instrumental in addressing complex business problems and supporting strategic decision-making. Furthermore, you will be tasked with developing and maintaining data governance frameworks, data quality standards, and data management practices to ensure the accuracy, integrity, and consistency of data assets. In this role, you will lead cross-functional teams in the design and delivery of data visualizations, dashboards, and reports that effectively communicate insights and drive action. It will be essential for you to stay updated with emerging trends, technologies, and best practices in data analytics and provide recommendations for their adoption to enhance analytical capabilities. Mentoring and coaching junior analysts to foster their professional growth and supporting their development of advanced analytical skills will also be part of your responsibilities. You will collaborate closely with data engineering teams to ensure efficient data collection, integration, and preparation for analysis purposes. Presenting complex findings, insights, and recommendations to senior leaders and stakeholders in a clear, concise, and compelling manner will be crucial. Moreover, you will play a key role in fostering a data-driven culture within the organization by promoting the value of data, advocating for data-driven decision-making, and driving data literacy initiatives. Requirements: - Bachelor's degree in a quantitative field such as Statistics, Mathematics, Economics, or Computer Science. A Master's or Ph.D. degree is strongly preferred. - 10+ years of extensive experience as a Data Analyst, with a significant portion of experience in a senior or lead role. - Proven track record of designing and implementing data analytics strategies and driving successful data-driven initiatives. - Expert proficiency in SQL for data extraction, manipulation, and analysis. - Advanced programming skills in Python/R for statistical analysis, predictive modeling, and machine learning. - In-depth knowledge of statistical analysis techniques, predictive modeling, and advanced machine learning algorithms. - Strong experience with data visualization tools such as Tableau, Power BI, or similar. - Extensive experience with data blending, preprocessing, and automation tools within PowerBi or similar. - Solid understanding of database structures, data warehousing concepts, and data governance principles. - Exceptional analytical and problem-solving skills, with the ability to tackle complex business challenges and provide innovative solutions. - Excellent leadership, strategic thinking, and stakeholder management abilities. - Exceptional communication and presentation skills, with the ability to influence and inspire stakeholders at all levels of the organization. - Proven ability to work independently, manage multiple projects, and prioritize effectively. Preferred Qualifications: - Experience in implementing data analytics solutions in cloud platforms such as AWS, Azure, or Google Cloud. - Knowledge of big data technologies such as Hadoop, Spark, or similar. - Familiarity with data science platforms and libraries (e.g., TensorFlow, PyTorch, scikit-learn). - Strong business acumen and the ability to align data analysis efforts with organizational goals and strategies. - Experience in leading and managing cross-functional teams.,

As a Senior Analyst - Data Analytics, you will leverage your 3+ years of experience in Data Analytics and reporting to design and build interactive dashboards and reports using Power BI and Microsoft Fabric. Your strong technical expertise in Power BI, Microsoft Fabric, Snowflake, SQL, Python, and R will be instrumental in performing advanced data analysis and visualization to support business decision-making. You will utilize your experience with Azure Data Factory, Databricks, Synapse Analytics, and AWS Glue to develop and maintain data pipelines and queries using SQL and Python. Applying data science techniques such as predictive modeling, classification, clustering, and regression, you will solve business problems and uncover actionable insights. Your hands-on experience in building and deploying machine learning models will be crucial in building, validating, and tuning machine learning models using tools such as scikit-learn, TensorFlow, or similar frameworks. Collaborating with stakeholders, you will translate business questions into data science problems and communicate findings in a clear, actionable manner. You will use statistical techniques and hypothesis testing to validate assumptions and support decision-making. Documenting data science workflows and maintaining the reproducibility of experiments and models will ensure the success of analytics projects. Additionally, you will support the Data Analytics Manager in delivering analytics projects and mentoring junior analysts. Professional certifications such as Microsoft Certified: Power BI Data Analyst Associate (PL-300), SnowPro Core Certification (Snowflake), Microsoft Certified: Azure Data Engineer Associate, and AWS Certified: Data Analytics Specialty are preferred or in progress to enhance your expertise in the field.,

You are looking for a Lead AI Engineer with at least 8 years of experience to join UST at Trivandrum. As a Lead AI Engineer, you will be responsible for designing and implementing end-to-end AI/ML solutions using Python and deep learning frameworks like Keras. Your role will involve working with Generative AI and LLM architectures such as GPT-3 and BERT, as well as leading AI/ML teams and mentoring junior engineers. Your key responsibilities will include developing data pipelines and infrastructure using tools like Kafka, Big Data tools, Aurora DB, and ELK Stack. You will also be expected to deploy and optimize ML models on cloud platforms such as AWS, Azure, or GCP. Your expertise in Time Series Forecasting, Predictive Analytics, and Deep Learning will be crucial in translating business requirements into scalable AI solutions. In addition to hands-on experience in AI and Machine Learning, you should have a strong programming background in Python, Keras, and Pandas. Knowledge of advanced ML models like LangChain, GPT-3, and Transformers, as well as analytical models such as Time Series Forecasting, will be highly beneficial. Familiarity with databases like ChromaDB/Pinecone is also desired. Experience with PoC creation, model experimentation, and AI governance principles will be an advantage. You should also keep abreast of emerging trends and tools in the AI/ML space to evaluate their strategic fit and contribute to AI roadmap planning. UST is a global digital transformation solutions provider known for partnering with leading companies to drive real impact through innovation. With a workforce of over 30,000 employees in 30 countries, UST is committed to embedding innovation and agility into its clients" organizations, touching billions of lives in the process.,

1. Job Purpose The Senior Data Analytics Analyst will play a key role in delivering hands-on analytics solutions across the UK and Ireland. This role focuses on bespoke report building, dashboard development, and advanced data analysis using technologies such as Power BI, Microsoft Fabric, Snowflake, Azure, AWS, Python, SQL, and R. Experience in data science is highly advantageous, including the application of machine learning and predictive modelling to solve business problems 2. Accountabilities & Activities • Design and build interactive dashboards and reports using Power BI and Microsoft Fabric. • Perform advanced data analysis and visualisation to support business decision-making. • Develop and maintain data pipelines and queries using SQL and Python. • Apply data science techniques such as predictive modelling, classification, clustering, and regression to solve business problems and uncover actionable insights. • Perform feature engineering and data preprocessing to prepare datasets for machine learning workflows. • Build, validate, and tune machine learning models using tools such as scikit-learn, TensorFlow, or similar frameworks. • Deploy models into production environments and monitor their performance over time, ensuring they deliver consistent value. • Collaborate with stakeholders to translate business questions into data science problems and communicate findings in a clear, actionable manner. • Use statistical techniques and hypothesis testing to validate assumptions and support decision-making. • Document data science workflows and maintain reproducibility of experiments and models. • Support the Data Analytics Manager in delivering analytics projects and mentoring junior analysts. • Design and build interactive dashboards and reports using Power BI and Microsoft Fabric. 3. Qualifications, Knowledge & Experience • Professional Certifications (preferred or in progress): - Microsoft Certified: Power BI Data Analyst Associate (PL-300) - SnowPro Core Certification (Snowflake) - Microsoft Certified: Azure Data Engineer Associate - AWS Certified: Data Analytics Specialty • Strong technical expertise in Power BI, Microsoft Fabric, Snowflake, SQL, Python, and R. • Experience with Azure Data Factory, Databricks, Synapse Analytics, and AWS Glue. • Hands-on experience in building and deploying machine learning models. • Ability to translate complex data into actionable insights. • Excellent problem-solving and communication skills. 4. Judgement Skills Balances team development with delivery priorities and business needs. Makes informed decisions on technical design, resource allocation, and delivery timelines. Evaluates project outcomes and identifies opportunities for team and process improvement. Encourages experimentation while maintaining delivery discipline and governance. 5. Freedom Of Action Acts as a key liaison between technical teams and business stakeholders. 6. Dimensions Financial: Supports budgeting and cost optimisation for analytics projects. Contributes to revenue growth through data-driven client solutions. Non-Financial: Drives adoption of modern analytics tools and practices. Builds strong relationships across business units and with external clients. 7. Environment Build strong relationships and influence key decision makers. Able to work under pressure and adapt to chang

Exp in SAS, SQL and large amounts of data US Stakeholder exp Exp of acquisition/account management credit risk models, transactional fraud models, marketing models, collections models, finance models, loss models, Loss forecasting (PD/LGD/EAD/CECL) Required Candidate profile SAS SQL Python Credit risk Credit Card Statistical Modelling Predictive Modelling

We are seeking a talented and experienced Senior Data Scientist specializing in handling massive tabular data on Large Language Models (LLMs) to join our clients team Mobilewalla, a global, fast-growing consumer data and technology company headquartered in Atlanta, GA, USA. You will play a crucial role in leveraging your expertise in tabular data analysis and LLMs to extract insights, build predictive models, and drive data-driven decisions at scale, especially for our Telco Vertical product. Collaborating closely with fellow engineers, you will contribute to the evolution of our platform by developing large-scale systems that process and act on massive amounts of data both in real-time and offline. Responsibilities: Utilize Large Language Models: Harness the power of Large Language Models (LLMs) to analyze massive volumes of tabular data efficiently and effectively. Tabular Data Analysis: Apply advanced statistical techniques and machine learning algorithms to uncover patterns, trends, and anomalies in complex tabular datasets. Predictive Modelling: Develop and deploy predictive models using LLMs to forecast future trends, identify potential risks, and optimize business outcomes based on large-scale tabular data. Data Handling and Pre-processing: Lead efforts in cleaning, pre-processing, and transforming raw tabular data to ensure quality, consistency, and scalability for analysis. Collaborative Problem-Solving: Collaborate closely with cross-functional teams to understand business challenges, formulate data-driven solutions, and drive actionable insights from tabular data. Product Enhancement: - Work closely with product managers to identify market trends and customer needs, translating them into actionable data science projects. - Provide data-driven recommendations to improve product features, user engagement, and overall customer satisfaction. Communication and Visualization: Effectively communicate findings, insights, and recommendations to non-technical stakeholders through clear visualizations, reports, and presentations. Mentorship and Leadership: Provide guidance, mentorship, and technical leadership to junior data scientists and team members, fostering a culture of learning and innovation. Qualifications: Educational Background: - Masters or Ph.D. in Data Science, Statistics, Computer Science, or a related field. Large Language Models (LLMs): Extensive experience working with Large Language Models (LLMs) such as GPT (Generative Pre-trained Transformer) for processing and analyzing tabular data at scale. Programming Proficiency: Strong proficiency in programming languages such as Python or R, with expertise in libraries such as PySpark, Pandas, NumPy, scikit-learn, and TensorFlow/PyTorch for data manipulation, analysis, and modeling. Experience: - Proven track record of at least 4-5 years in a data science role with a focus on Telco competitive intelligence products. - Strong experience in applying machine learning algorithms and statistical modeling in the Telco domain. Technical Skills: - Proficiency in programming languages such as Python or R. - Hands-on experience with relevant machine learning libraries (e.g., TensorFlow, PyTorch, PySpark) and data manipulation tools. Domain Knowledge: - In-depth understanding of Telecommunications industry trends, challenges, and emerging technologies. - Familiarity with Telco-specific datasets and data sources. Preferred Qualification: - Experience with Location Intelligence, including geospatial analytics, GIS tools, and the application of location-based data in Telco products. Collaboration: - Proven ability to collaborate effectively with cross-functional teams, including product management, engineering, and business stakeholders. Communication Skills: - Excellent communication skills with the ability to present complex technical findings in a clear and understandable manner. If you are a passionate & innovative problem solver with expertise in Telco products, we invite you to join the team and contribute to the success of our cutting-edge products in the telecommunications space.,

As a Healthcare Technology Organization dedicated to simplifying, accelerating, and optimizing care delivery for healthcare enterprises, AVIZVA has been a strategic enabler in the industry since 2011. With a proven track record of over 13 years, we have designed and delivered more than 150 customized products for prominent Medical Health Plans, Dental and Vision Plan Providers, PBMs, Medicare Plan Providers, TPAs, and other healthcare entities. In your role as an Associate Manager - Applied Machine Learning at AVIZVA, you will be at the forefront of architecting, designing, and developing advanced GenAI products and services. Your responsibilities will include leveraging your technical expertise in machine learning to lead a team effectively and contribute to the development of Large Language Model (LLM) based products. By combining GenAI and traditional ML approaches, you will play a crucial role in meeting key product requirements. Collaboration is key in this role, as you will work closely with cross-functional teams, including product managers and business leaders, to deliver scalable machine-learning solutions that align with business objectives. **Job Responsibilities:** - Lead the team by setting clear goals, priorities, and performance expectations that align with business objectives. - Architect and oversee the lifecycle of LLM based GenAI projects, ensuring timely delivery in line with business needs. - Take ownership of technical and operational challenges, providing solutions to keep projects on track. - Collaborate with infrastructure and engineering teams to seamlessly deploy and integrate models into production environments. - Foster a culture of continuous improvement through agile practices and regular retrospectives. - Stay updated on emerging machine learning technologies and prototype new algorithms to tackle complex challenges. - Motivate the team to deliver high-quality results on time while maintaining a collaborative work environment. **Skills & Qualifications:** - Bachelor's or Master's degree in Computer Science or a related analytical field. - Minimum of 1 year of experience in Gen AI, Agentic AI, and Large Language Models. - Hands-on experience in building RAG pipelines and utilizing NLP, NLG, Text Analytics, and Transformer-based models. - 10+ years of experience as an Applied Machine Learning Engineer or Data Scientist, with expertise in Python. - Strong knowledge of system design, architecture, design principles, and Core Python. - Proficiency in ensemble models, classification, clustering algorithms, and Object-Oriented Programming. - Experience with ORM tools, RESTful services, debugging, testing frameworks, and web development. - Familiarity with Agile methodology, excellent communication, and problem-solving skills. Join AVIZVA to be a part of a dynamic team that is dedicated to transforming healthcare delivery through innovative technology solutions.,

As a DevOps Engineer for AI products at Linde, you will play a crucial role in the Artificial Intelligence team within Linde's global corporate division. You will collaborate with a diverse international team consisting of Project Managers, Data Scientists, Data and Software Engineers, and other professionals. Your responsibilities will include designing, implementing, and managing robust CI/CD pipelines to support the deployment of AI and data-driven applications globally. You will be tasked with administering and monitoring cloud-based infrastructure to ensure high availability, security, and cost-efficiency of AI product deployments. Additionally, your role will involve developing and maintaining containerized environments using Docker, orchestrating deployment strategies, and establishing infrastructure monitoring and logging solutions for AI platforms in production. It is essential that all DevOps practices adhere to Linde's security guidelines and industry best practices. To succeed in this role, you should have a Bachelor's degree or equivalent experience in a related field such as Statistics, Mathematics, Computer Science, or Engineering. You must possess a good understanding of modern web applications, cloud platforms (Azure, AWS, GCP), Docker, CI/CD pipelines, and database deployments. Experience with automation tools like Azure DevOps and Github Actions is required, along with strong communication skills in English. Linde is a renowned global industrial gases and engineering company operating in over 100 countries. By joining Linde, you will have the opportunity to work on cutting-edge projects that make the world more productive while contributing to sustainability and environmental protection. If you are looking for a career where your work transcends boundaries and positively impacts the world, Linde offers limitless opportunities for growth and development. If you are inspired to be part of a dynamic team that values innovation and excellence, we encourage you to submit your complete application (motivation letter, CV, certificates) through our online job market. At Linde, we are committed to fostering a diverse and inclusive workplace where individuals of all genders can thrive and succeed. Join us at Linde and unleash your potential to make a meaningful difference in the world.,

The Data Science team at Meesho plays a crucial role in devising creative solutions and building intelligent systems for millions of users across a wide range of product categories. As a Principal Data Scientist in the AdTech team, you will lead innovation in the advertising platform by leveraging advanced machine learning and statistical methods. Your responsibilities will include developing algorithms to optimize ad spend and ROI, designing frameworks to measure ad effectiveness, collaborating with cross-functional teams to implement AI/ML solutions, and providing strategic insights to tech and business leadership. Key Responsibilities: - Design and develop sophisticated algorithms for bidding and budget optimization. - Create frameworks for measuring ad effectiveness and ROI. - Collaborate with product and engineering teams to implement AI/ML solutions. - Communicate insights and recommendations to tech and business leadership. - Mentor junior data scientists and provide technical guidance. - Lead research initiatives in machine learning, auction theory, and advertising technology. Requirements: - B.Tech in Computer Science, Machine Learning, or a related field with a minimum of 6 years of experience in AI/ML research. - Proficiency in PyTorch or TensorFlow, and expertise in Python and big data technologies. - Experience in auction theory, predictive modeling, causal inference, and reinforcement learning. - Strong communication skills to convey complex concepts to technical and non-technical audiences. - Prior experience in mentoring junior data scientists and managing multiple problem statements. Preferred Qualifications: - M.Tech or Ph.D. in Computer Science with a specialization in Machine Learning. - 3+ years of experience applying machine learning in AdTech or related domains. - Exposure to real-time bidding systems, programmatic advertising, or ad exchanges. - Track record of successful research-to-product transitions. - Strong publication record in top AI conferences (e.g., NeurIPS, ICML, ICLR, KDD, CVPR, AAAI).,

Develop mathematical models for trading, forecasting, or data processing, and continuously enhance existing models. Analyze large datasets to identify trends and insights, as well as conduct research on financial markets and economic conditions. Utilize strong coding skills in Python and other languages to implement mathematical models. Explore unconventional data sources to drive innovation and enhance model performance. Translate mathematical models into algorithms for practical application. Manage risk by developing mathematical models to assess and mitigate risks associated with products or strategies. Build predictive models based on historical data using Monte Carlo modeling techniques. Demonstrate proficiency in writing pseudo code and Python code to test mathematical models. Possess a good understanding of trading systems and trade execution processes to minimize latency and slippages. Have a comprehensive knowledge of financial and capital markets to make informed decisions. Oversee the development and implementation of investment strategies using mathematical and statistical tools. Utilize AI, machine learning, and linear latent models to enhance efficiency and productivity. Apply data science, mathematics, and statistics to develop or enhance investment strategies. Ensure compliance with SEBI regulations and other legal requirements. Identify and implement mathematical and statistical models for effective risk management of strategies and products. Establish and monitor internal controls to manage and mitigate risks efficiently. Requirements: - Bachelor's degree in Mathematics, Master's degree preferred or currently pursuing a PhD in Mathematics. - Relevant experience in mathematics, statistics, computer science, or finance is preferred. - Minimum of 3-5 years of experience in building mathematical models and data sciences. - Proven ability to develop and implement mathematical models in live market strategies. - Uphold high ethical standards and prioritize clients" best interests. This is a full-time position with a day shift schedule requiring in-person work.,

As a member of our team, you will be responsible for managing organizational strategy and operations through the design and statistical analysis of business initiatives and experiments. Your role will involve collaborating with business partners to understand and address their needs and issues effectively. Utilizing advanced knowledge of statistics and data mining techniques, such as predictive modeling and simulation, you will identify patterns and insights from business data. Additionally, you will be tasked with designing, developing, and evaluating statistical and predictive models to drive business solutions. In this position, you will act as the lead statistician for the unit, providing expertise, oversight, and guidance on statistical analysis efforts. Communication of findings and recommendations to management across various departments will be a crucial aspect of your role. Furthermore, you will support implementation efforts and lead and mentor the team working in the Data Competency Centre. To excel in this role, you should possess a Bachelor's degree in data science, computer science, electrical engineering, applied statistics, or physics with 8-10 years of relevant work experience in Data Science, Artificial Intelligence, or Machine Learning algorithm development. Alternatively, a Master's degree with 5+ years of relevant work experience or a PhD with 4+ years of relevant work experience in the aforementioned fields will also be considered. A working knowledge of budgets and financial statements is required. Key skills and competencies for this position include demonstrated experience in managing teams, coaching team members to drive results, proficiency in programming languages and statistical software tools (such as Python, SAS, R, JMP), relational databases (SQL server), and data analysis and visualization software (preferably PowerBI, SAS). You should also have experience with standard data science and machine learning packages, as well as machine learning model tradeoffs and computer vision models. Strong communication skills are essential to effectively collaborate with various business partners and communicate complex data relationships and statistical model results. Your essential responsibilities will involve statistical analysis and model development in collaboration with business partners, internal teams, and Enterprise Data Management. You will explore data using statistical techniques to answer business questions, build hypotheses, and identify research data attributes. Additionally, you will lead the development of experimental designs for business initiatives, apply advanced statistical techniques, build predictive models, and deploy computer vision models to meet business needs. Providing guidance and direction related to statistical analysis, as well as effectively communicating and delivering statistical and predictive model results to business partners, are critical aspects of this role. You will report to the Head of Automation Digital Transformation USA and will have direct reports. Some travel may be required for this position. This is a full-time role based in Plot No.A-1/1 SIPCOT Industrial Park, Sriperumbudur, Tamil Nadu, 602105, IN. If you believe you meet the qualifications and can excel in fulfilling the responsibilities outlined for this role, we encourage you to apply. All candidates receiving an offer of employment must successfully complete a background check and any other required tests. Job Identification: 1021960 Job Category: NPI-HSRT Integration Data Science Posting Date: 07/17/2025, 12:17 AM Job Schedule: Full time Work Schedule: Normal Shift New (PMT),

This position offers an excellent career opportunity for a computational chemist to leverage quantum chemistry skills in chemical process optimization and product development in the agrochemical industry. You should have a thorough understanding of DFT and ab initio electronic structure theory methods. Proficiency with Quantum Chemistry based software tools like Turbomole, Gaussian, deMon, GAMESS-US, Quantum espresso, VASP, etc. is required. Additionally, you should have proficiency with any of the scripting languages like Bash, Python, Perl, etc. and working in a Linux environment and high-performance computing platforms. Demonstrated experience in using electronic structure based software tools in understanding chemical reactivity and reaction mechanisms is essential. Experience in catalyst design and the use of data-based models to optimize industrial processes is preferred. Moreover, experience in utilizing in-house experimental data and modelled parameters towards predictive modeling and statistics would be a plus. You should have a working knowledge of classical methods like force fields and molecular dynamics simulations. The ability to work in a collaborative multidisciplinary scientific environment and communicate technical results to experimentalists is crucial for this role. The ideal candidate should have 3+ years of postdoc or industrial experience in a related field, with a PhD in Chemistry/Physics specializing in Theoretical Chemistry/Computational Chemistry/Chemical Physics or a related discipline from a reputed University/Institute in India or overseas with excellent academic credentials.,

As a Senior Data Scientist with a focus on Predictive Analytics and expertise in Databricks, your primary responsibilities will involve designing and implementing predictive models for various applications such as forecasting, churn analysis, and fraud detection. You will utilize tools like Python, SQL, Spark MLlib, and Databricks ML to deploy these models effectively. Your role will also include building end-to-end machine learning pipelines on the Databricks Lakehouse platform, encompassing data ingestion, feature engineering, model training, and deployment. It will be essential to optimize model performance through techniques like hyperparameter tuning, AutoML, and leveraging MLflow for tracking. Collaboration with engineering teams will be a key aspect of your job to ensure the operationalization of models, both in batch and real-time scenarios, using Databricks Jobs or REST APIs. You will be responsible for implementing Delta Lake to support scalable and ACID-compliant data workflows, as well as enabling CI/CD for machine learning pipelines using Databricks Repos and GitHub Actions. In addition to your technical duties, troubleshooting Spark Jobs and resolving issues within the Databricks Environment will be part of your routine tasks. To excel in this role, you should possess 3 to 5 years of experience in predictive analytics, with a strong background in regression, classification, and time-series modeling. Hands-on experience with Databricks Runtime for ML, Spark SQL, and PySpark is crucial for success in this position. Familiarity with tools like MLflow, Feature Store, and Unity Catalog for governance purposes will be advantageous. Industry experience in Life Insurance or Property & Casualty (P&C) is preferred, and holding a certification as a Databricks Certified ML Practitioner would be considered a plus. Your technical skill set should include proficiency in Python, PySpark, MLflow, and Databricks AutoML. Expertise in predictive modeling techniques such as classification, clustering, regression, time series analysis, and NLP is required. Familiarity with cloud platforms like Azure or AWS, Delta Lake, and Unity Catalog will also be beneficial for this role.,

We are seeking a highly skilled and experienced Business Analytics and Insights Manager to drive data-driven business strategies, empower decision-making, and enhance customer experiences for our enterprise products. Your role will involve leveraging advanced analytics, predictive modeling, and data integration to provide actionable insights aligned with business objectives. You will be responsible for predicting business trends, forecasting performance, and providing data-backed recommendations to improve revenue attainment, customer retention, and sales performance. Additionally, you will lead efforts to establish seamless integrations between data sources, data catalogue systems, and analytics tools to drive insights and innovation. You will be expected to: - Deliver actionable insights and dashboards using tools like Power BI, KNIME, Tableau, and similar analytics platforms - Communicate insights to Success Managers, Product Leaders, and Customer Experience Executives through engaging visualizations and data stories - Support leadership with data-driven recommendations to enhance decision-making and strategic planning You will also: - Analyze historical and real-time data to develop predictive models and forecasts for business value growth, revenue attainment, and customer experience improvement - Identify renewal trends, churn risks, and upsell/cross-sell opportunities through data-driven insights - Provide forward-looking recommendations to mitigate risks and optimize performance Furthermore, you will: - Establish and manage integrations across data sources, ensuring a unified data view - Build, maintain, and optimize data pipelines, warehouses, and catalog systems for scalable analytics - Implement robust data governance frameworks to ensure data integrity, accuracy, and security You will leverage advanced analytics platforms and AI/ML capabilities to generate predictive and prescriptive insights. Your role will involve developing forecasting models to anticipate business trends, revenue outcomes, and customer behavior, as well as driving corrective and preventive strategies based on analytics. Collaboration with cross-functional teams to understand business challenges, providing strategic insights to senior leadership, and fostering a culture of data-driven decision-making will be key aspects of your role. Qualifications and Skills: - Education: Bachelors or Masters degree in Statistics, Computer Science, Data Science, Business Analytics, or a related field - Experience: 13-15 years in data analytics, business intelligence, or related domains, with expertise in predictive analytics and forecasting, preferably in a B2B SaaS environment - Technical Expertise: Proficiency in analytics and visualization tools, expertise in AI/ML platforms, and strong understanding of data management and governance frameworks - Functional Knowledge: Deep understanding of customer lifecycle management, business performance metrics, and ability to translate data into actionable insights for strategy and performance improvement,

You will play a crucial role in developing and maintaining descriptive and predictive analytics models and tools that support Lowe's pricing strategy. Working closely with the Pricing team, you will translate pricing goals and objectives into data and analytics requirements. By leveraging a combination of open source and commercial data science tools, you will gather and wrangle data to provide data-driven insights, trends, and identify anomalies. Utilizing suitable statistical and machine learning techniques, you will address relevant questions and offer retail recommendations. Collaboration with product and business teams is essential to drive continuous improvement, incorporating feedback throughout development to maintain a best-in-class position in the pricing space. Your responsibilities will include translating pricing strategy and business objectives into analytics requirements, implementing processes for data collection and preparation, conducting data validation and outlier detection, designing and implementing statistical and machine learning models, ensuring model accuracy, and applying machine learning outcomes to business use cases. Educating the pricing team on interpreting and utilizing machine learning model results, designing and executing experiments to evaluate price changes, performing advanced statistical analyses, and managing analytics projects are key aspects of this role. You will also lead the exploration of new analytical techniques, collaborate with various teams, stay updated on industry developments, and mentor junior analysts to foster skill development and team growth. With 6-12 years of relevant experience, you should hold a Bachelor's or Master's degree in Engineering, Business Analytics, Data Science, Statistics, Economics, or Mathematics. Your skill set should include expertise in advanced quantitative analysis, statistical modeling, and machine learning models, along with experience in regression, hypothesis testing, time series analysis, predictive modeling, and other analytical concepts. Proficiency in SQL, Python, R, SAS, enterprise-level databases, data visualization tools, and cloud platforms is required. Technical expertise in Alteryx and Knime is desired for this role.,

The ideal candidate must possess strong expertise in Alteryx, with the ability to create complex workflows, perform data preparation, blending, and modeling. Additionally, they should be proficient in creating and publishing PowerBI dashboards, well-versed in DAX and M-Query, and skilled in sourcing data from various platforms while building data models. A good understanding of SQL and SQL databases is also required. Having excellent data sense, conceptual, and logical abilities is essential for this role, along with experience and exposure to Data Warehousing and Data Modeling. Knowledge of Predictive Modeling techniques such as Forecasting, Regression, and Classification is a plus. Moreover, coding experience in any language would be beneficial. The responsibilities of this position include understanding underlying business requirements, designing, and executing analytical solutions to support these requirements. The candidate will be responsible for accessing and extracting data from diverse sources using SQL, APIs, etc., and transforming raw data into analysis-ready datasets. They will also be required to connect to different data sources, extract and transform data for report development, and create visualizations using Power BI, Alteryx to derive insightful analysis. Furthermore, the candidate should be proficient in problem-solving and data analysis, with experience in modeling and statistics. Working knowledge of Python/R and experience in analytical modeling through SAS/Python are desired. It is essential to document and communicate analytical approaches and solutions effectively across various teams, analyze large datasets, and develop solutions based on data insights. Qualifications for this role include a degree in BE/BTECH, MCA, MBA from a reputable institute, with a preference for a Masters's in Data Analytics degree. Relevant Data Analytics Certification(s) would be a plus. The candidate should have 5 to 9 years of work experience in a relevant field. #KGS,

Exp in SAS, SQL and large amounts of data US Stakeholder exp Exp of acquisition/account management credit risk models, transactional fraud models, marketing models, collections models, finance models, loss models, Loss forecasting (PD/LGD/EAD/CECL) Required Candidate profile SAS SQL Python Credit risk Credit Card Statistical Modelling Predictive Modelling

Location:Bangalore/Gurgaon/Hyderabad/Mumbai Must have skills: Must have skills:Data Scientist / Transformation Leader & at least 5 years in Telecom Analytics Good to have skills:GEN AI, Agentic AI, Job Summary : About Global Network Data & AI:- Accenture Strategy & Consulting Global Network - Data & AI practice help our clients grow their business in entirely new ways. Analytics enables our clients to achieve high performance through insights from data - insights that inform better decisions and strengthen customer relationships. From strategy to execution, Accenture works with organizations to develop analytic capabilities - from accessing and reporting on data to predictive modelling - to outperform the competition About Comms & Media practice: Comms & Media (C&M) is one of the Industry Practices within Accentures S&C Global Network team. It focuses in serving clients across specific Industries Communications, Media & Entertainment. Communications Focuses primarily on industries related with telecommunications and information & communication technology (ICT). This team serves most of the worlds leading wireline, wireless, cable and satellite communications and service providers Media & Entertainment Focuses on industries like broadcast, entertainment, print and publishing Globally, Accenture Comms & Media practice works to develop value growth strategies for its clients and infuse AI & GenAI to help deliver top their business imperatives i.e., revenue growth & cost reduction. From multi-year Data & AI transformation projects to shorter more agile engagements, we have a rapidly expanding portfolio of hyper-growth clients and an increasing footprint with next-gen solutions and industry practices. Roles & Responsibilities: A Telco domain experienced and data science consultant is responsible to help the clients with designing & delivering AI solutions. He/she should be strong in Telco domain, AI fundamentals and should have good hands-on experience working with the following: Ability to work with large data sets and present conclusions to key stakeholders; Data management using SQL. Propose solutions to the client based on gap analysis for the existing Telco platforms that can generate long term & sustainable value to the client. Gather business requirements from client stakeholders via interactions like interviews and workshops with all stakeholders Track down and read all previous information on the problem or issue in question. Explore obvious and known avenues thoroughly. Ask a series of probing questions to get to the root of a problem. Ability to understand the as-is process; understand issues with the processes which can be resolved either through Data & AI or process solutions and design detail level to-be state Understand customer needs and identify/translate them to business requirements (business requirement definition), business process flows and functional requirements and be able to inform the best approach to the problem. Adopt a clear and systematic approach to complex issues (i.e. A leads to B leads to C). Analyze relationships between several parts of a problem or situation. Anticipate obstacles and identify a critical path for a project. Independently able to deliver products and services that empower clients to implement effective solutions. Makes specific changes and improvements to processes or own work to achieve more. Work with other team members and make deliberate efforts to keep others up to date. Establish a consistent and collaborative presence with clients and act as the primary point of contact for assigned clients; escalate, track, and solve client issues. Partner with clients to understand end clients business goals, marketing objectives, and competitive constraints. Storytelling Crunch the data & numbers to craft a story to be presented to senior client stakeholders. Professional & Technical Skills: Overall 10+ years of experience in Data Science & at least 5 years in Telecom Analytics Masters (MBA/MSc/MTech) from a Tier 1/Tier 2 and Engineering from Tier 1 school Demonstrated experience in solving real-world data problems through Data & AI Direct onsite experience (i.e., experience of facing client inside client offices in India or abroad) is mandatory. Please note we are looking for client facing roles. Proficiency with data mining, mathematics, and statistical analysis Advanced pattern recognition and predictive modeling experience; knowledge of Advanced analytical fields in text mining, Image recognition, video analytics, IoT etc. Execution level understanding of econometric/statistical modeling packages Traditional techniques like Linear/logistic regression, multivariate statistical analysis, time series techniques, fixed/Random effect modelling. Machine learning techniques like - Random Forest, Gradient Boosting, XG boost, decision trees, clustering etc. Knowledge of Deep learning modeling techniques like RNN, CNN etc. Experience using digital & statistical modeling software (one or more) Python, R, PySpark, SQL, BigQuery, Vertex AI Proficient in Excel, MS word, Power point, and corporate soft skills Knowledge of Dashboard creation platforms Excel, tableau, Power BI etc. Excellent written and oral communication skills with ability to clearly communicate ideas and results to non-technical stakeholders. Strong analytical, problem-solving skills and good communication skills Self-Starter with ability to work independently across multiple projects and set priorities Strong team player Proactive and solution oriented, able to guide junior team members. Execution knowledge of optimization techniques is a good-to-have Exact optimization Linear, Non-linear optimization techniques Evolutionary optimization Both population and search-based algorithms Cloud platform Certification, experience in Computer Vision are good-to-haves Qualification Experience: Overall 10+ years of experience in Data Science & at least 5 years in Telecom Educational Qualification: Masters (MBA/MSc/MTech) from a Tier 1/Tier 2 and Engineering from Tier 1 school

Exp in SAS, SQL and large amounts of data US Stakeholder exp Exp of acquisition/account management credit risk models, transactional fraud models, marketing models, collections models, finance models, loss models, Loss forecasting (PD/LGD/EAD/CECL) Required Candidate profile SAS SQL Python Credit risk Credit Card Statistical Modelling Predictive Modelling