1169 Statistical Modeling Jobs - Page 44

Project Role :Cloud Platform Engineer Project Role Description : Designs, builds, tests, and deploys cloud application solutions that integrate cloud and non-cloud infrastructure. Can deploy infrastructure and platform environments, creates a proof of architecture to test architecture viability, security and performance. Must have skills : NEXThink Good to have skills : NAMinimum 5 year(s) of experience is required Educational Qualification : 15 years full time education Summary :As a Cloud Platform Engineer, you will be responsible for designing, building, testing, and deploying cloud application solutions that seamlessly integrate both cloud and non-cloud infrastructure. Your typical day will involve collaborating with various teams to ensure the architecture's viability, security, and performance while creating proof of concepts to validate your designs. You will engage in hands-on deployment of infrastructure and platform environments, ensuring that all components work harmoniously together to meet organizational goals. Your role will also require you to stay updated with the latest cloud technologies and best practices to enhance the efficiency and effectiveness of the solutions you develop. Roles & Responsibilities:- Expected to be an SME.- Collaborate and manage the team to perform.- Responsible for team decisions.- Engage with multiple teams and contribute on key decisions.- Provide solutions to problems for their immediate team and across multiple teams.- Mentor junior professionals to enhance their skills and knowledge in cloud technologies.- Continuously evaluate and improve cloud application solutions to ensure optimal performance and security. Professional & Technical Skills: - Must To Have Skills: Proficiency in NEXThink.- Good To Have Skills: Experience with cloud service providers such as AWS, Azure, or Google Cloud Platform.- Strong understanding of cloud architecture and deployment models.- Experience with automation tools and scripting languages to streamline deployment processes.- Familiarity with monitoring and performance tuning of cloud applications. Additional Information:- The candidate should have minimum 5 years of experience in NEXThink.- This position is based at our Bengaluru office.- A 15 years full time education is required. Qualification 15 years full time education

Project Role :Data Science Practitioner Project Role Description : Formulating, design and deliver AI/ML-based decision-making frameworks and models for business outcomes. Measure and justify AI/ML based solution values. Must have skills : Python (Programming Language) Good to have skills : NAMinimum 12 year(s) of experience is required Educational Qualification : 15 years full time education Summary :As a Data Science Practitioner, you will be engaged in formulating, designing, and delivering AI and machine learning-based decision-making frameworks and models that drive business outcomes. Your typical day will involve collaborating with various teams to measure and justify the value of AI and machine learning solutions, ensuring that they align with organizational goals and deliver tangible results. You will also be responsible for analyzing data, developing algorithms, and presenting insights that support strategic decision-making processes within the organization. Roles & Responsibilities:- Expected to be an SME.- Collaborate and manage the team to perform.- Responsible for team decisions.- Engage with multiple teams and contribute on key decisions.- Expected to provide solutions to problems that apply across multiple teams.- Facilitate knowledge sharing and mentorship within the team to enhance overall performance.- Continuously evaluate and improve existing AI/ML models to ensure optimal performance and relevance. Professional & Technical Skills: - Must To Have Skills: Proficiency in Python (Programming Language).- Strong understanding of machine learning algorithms and their applications.- Experience with data analysis and statistical modeling techniques.- Familiarity with data visualization tools to effectively communicate insights.- Ability to work with large datasets and perform data preprocessing tasks. Additional Information:- The candidate should have minimum 12 years of experience in Python (Programming Language).- This position is based at our Bengaluru office.- A 15 years full time education is required. Qualification 15 years full time education

We are looking for a highly skilled Data Scientist with expertise in Python and MATLAB to join our team at Apex One. The ideal candidate will have 2-5 years of experience in the field. Roles and Responsibility Develop and implement data models using Python and MATLAB. Analyze large datasets to extract insights and trends. Collaborate with cross-functional teams to integrate data into business operations. Design and implement data visualizations to communicate complex data insights. Work closely with stakeholders to identify business problems and develop solutions. Stay updated with industry trends and emerging technologies in data science. Job Requirements Strong proficiency in Python and MATLAB programming languages. Experience with data analysis, modeling, and visualization tools. Excellent problem-solving skills and attention to detail. Ability to work collaboratively in a team environment. Strong communication and interpersonal skills. Experience with data management and database systems.

Responsibilities: Collaborate with business stakeholders to understanddatarequirements and objectives. Analyse complexdatasets to extract valuable insights and trends. Interpretdatato identify opportunities for process improvements and business growth. Develop reports, dashboards, and visualisations to communicate findings effectively. Conductdataquality assessments and ensuredataintegrity across systems. Supportdata-driven decision-making by providing actionable recommendations. Work with cross-functional teams to implementdatasolutions that meet business needs. Stay informed on industry trends and best practices indataanalysis and business intelligence Qualifications: Bachelor's degree in Business Administration, Statistics, Computer Science, or related field. Proven experience as a BusinessAnalystorDataAnalystin a corporate setting. Proficiency indataanalysis tools (e.g., SQL, Excel, Amazon QuickSight) anddatabase querying. Strong analytical skills with the ability to translate complexdatainto actionable insights. Excellent communication and presentation skills. Experience withdatavisualization tools and techniques. Knowledge of business processes and operations. Preferred Skills: Familiarity with ETL processes anddatawarehousing concepts. Experience with predictive analytics and statistical modelling. Certification in business analysis or related field is a plus. Knowledge of Agile methodologies for project management.

Generative AI Experience in developing Generative AI based applications Knowledge of various GenAI techniques and frameworks. Python o Machine Learning model development and deployment Azure AI services Optional skills but good to have : SQL API development

Primary Responsibilities: Play technical leading role and hands-on for researching, designing, implementing and deploying full-stack scalable machine learning solutions to support house call member engagements Design and develop the enterprise scalable intelligent solutions to drive increasing business values. Work with a great deal of autonomy to find solutions to complex problems Effectively communicate complex technical results to business partners Consolidate internal and external data to establish member journey line across different programs Establish machine learning/deep learning models to increase member outbound reach experience and NPS scores, implement the solutions into applications or operation Provide training and consultation for other junior team members Comply with the terms and conditions of the employment contract, company policies and procedures, and any and all directives (such as, but not limited to, transfer and/or re-assignment to different work locations, change in teams and/or work shifts, policies in regards to flexibility of work benefits and/or work environment, alternative work arrangements, and other decisions that may arise due to the changing business environment). The Company may adopt, vary or rescind these policies and directives in its absolute discretion and without any limitation (implied or otherwise) on its ability to do so Required Qualifications: Bachelors degree in Applied Mathematics, Statistics, Computer Sciences, Information Management, Actuarial Science or a related technical field 5+ years of experience in machine learning modeling and data analytics. 5 years of experience in creating full stack of machine learning end-to-end model pipeline 5 years of experience leading technical and non-technical resources in the area of Information Management, Data Strategy, Business Intelligence development, data mining and predictive analytics with machine learning/statistical modeling techniques 3+ years of experience in Python. Experience working for a large enterprise with fragmented data sources, lack of documentation, unstructured requirements and ambiguity Experience working with business stakeholders and leaders in understanding data analytics and information needs, and executing on transformation of high-level, abstract data needs into meaningful data management solutions, information and analysis Experience understanding and managing business data and information, and the ability to correlate business processes to data Experience converting raw data into processed, actionable, insightful information Basic knowledge of machine learning and data processing services from cloud providers such as Amazon Web Services, Google Cloud, and Microsoft Azure Proven solid ability to communicate highly technical issues/results to a diverse audience both verbally and in written Proven solid execution mentality Preferred Qualifications: MS in Applied Mathematics, Physics, Computer Sciences, Information Management, Statistics, Actuarial Science or a related technical field Experienced in Speech Recognition modeling and/or Natural Language Process Proven engineering background

Data Scientists Responsibilities: The data scientists will be responsible for modeling complex problems, discovering insights and identifying opportunities through the use of statistical, machine learning, algorithmic, data mining and visualization techniques. They are also responsible for moving the models to production environment and automate with appropriate drift monitoring and model improvement process. They will need to collaborate effectively with internal stakeholders and cross-functional teams to understand requirements, solve problems, create operational efficiencies, and deliver successfully against high organizational standards. The candidates should be able to apply a breadth of tools, data sources and analytical techniques to answer a wide range of high-impact business questions and present the insights in concise and effective manner. The candidates should be an effective communicator capable of independently driving issues to resolution, communicating insights to non-technical audiences and documenting the artifacts. This is a high impact role with goals that directly impacts the bottom line of the business. Data Scientists: Development of accurate and reliable workforceforecasting models. Automate training and forecasting by deploying data and model pipelines on AWS cloud infrastructure with drift monitoring with emphasis on accuracy and speed Building Project launch impact estimates modelusing tools such as of analytics, time series, probability and deep learning. Reduce MAPE (forecasting accuracy) acrossdifferent risk functions. Automate data ingestion for Project inputs from Excel to forecasting models Improved data quality through rigorous cleaning and transformation processes and automating them. Clear documentation of the code and artifacts. Actionable insights derived from data analysis to support strategic decisions. Experiment with latest forecasting algorithms & processes to optimize existing modeling infrastructure. Qualifications Needed Data Scientists: 5+ years of data scientist experience, preferably with Forecasting systems & Operational Research 3+ years of data querying languages (e.g. SQL) and scripting languages (e.g. Python) experience 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience Experience applying theoretical models in an applied environment Understanding of demand forecasting & impact on operational capacity planning Knowledge of time series models and deep learning for time series are an asset

Analytics professional in payment integrity - stats and modeling data analytics team. Person will be responsible for delivering various fraud analytics statistical projects based on US healthcare data and other consulting assignment. These projects may involve model development, validation, governance, implementation and end to end delivery Lead and work closely with junior/senior statisticians to deliver Fraud, Waste, Abuse (FWA) statistical projects. Team builds models through advanced statistical techniques. Provide support to management in business development, client proposals and in building solid relationships with global analytics teams. Expert in data analytics with significant amount of project delivery skills in one or more of the following areas: Model Building, Model Validation, Fraud detection Analytics, Risk Analytics, Multivariate Analysis Primary Responsibilities: Collaborates across business units with stakeholders, providing thought leadership, and driving day-to-day implementation of our analytics strategy Demonstrable leadership ability, superior problem solving and people management skills. Evaluate statistical methods used to obtain the data to ensure validity, applicability, efficiency and accuracy. Interpret end-user technical requirements by specifying economic decision models, determining appropriate data sources, and performing detailed statistical analysis Create, analyze and maintain explanatory/predictive models of clinical behaviours on healthcare claims data. Work includes all phases of the modelling process: research design, data extraction and cleaning, model building and validation Research on the new fraud & abuse patterns and ideate new assignments/projects basis the secondary/data driven research Lead the advanced statistics domain for the team & develop/refine/improve predictive models using advance SAS, Python, Spark & machine learning techniques and mentors junior/senior analysts/statisticians to develop their modeling/statistical skills Maintains staff by recruiting, selecting, orienting, and training employees; maintaining a safe, secure, and legal work environment; developing personal growth opportunities and accomplishes staff results by communicating job expectations; planning, monitoring, and appraising job results; coaching, counseling, and disciplining employees; developing, coordinating, and enforcing systems, policies, procedures, and productivity standards Co-ordinate with clinical/Coding SMEs for seeking the inputs to explore data extraction approach and road map the analysis milestones Develop and maintain working relationships with key customer stakeholders Comply with the terms and conditions of the employment contract, company policies and procedures, and any and all directives (such as, but not limited to, transfer and/or re-assignment to different work locations, change in teams and/or work shifts, policies in regards to flexibility of work benefits and/or work environment, alternative work arrangements, and other decisions that may arise due to the changing business environment). The Company may adopt, vary or rescind these policies and directives in its absolute discretion and without any limitation (implied or otherwise) on its ability to do so Required Qualifications: Masters degree in math or statistics from top universities (Tier I/II) with solid record of achievement and approximately 1+ years of relevant work experience 2+ years of work experience in the area(s) of statistical analysis, data modelling 1+ years of project management experience Experience in data analytics, predictive & statistical modeling, strategy, project management, team management and business development Experience comprising analytics service delivery, solution design and client management Expert focused on helping team improve modeling predictability, analytics driven strategy development, operational efficiency Knowledge of statistical tools and techniques, especially those relating to data mining & analysis. Should have ability to handle/work on large data sets Displays solid communication, interpersonal, and leadership ability across all levels coupled with effective problem solving, conceptual thinking, quantitative and analytical skills Demonstrated leadership ability and willingness to take initiative Excellent knowledge of SAS, Python/Spark, or any other statistical software to carry out analysis and drive conclusions Solid understanding and implementation experience on predictive modeling algorithms such as time series, neural networks, clustering, decision trees, heuristic models, with familiarity dealing with trade-off between model performance and business needs Solid project management skills, ability to influence cross-functionally in a rapidly evolving business environment while managing multiple/concurrent projects Must be able to communicate ideas effectively and concisely to all levels of Management, business partners, and to other external clients Ability to work independently and with a team Preferred Qualifications: Experience/interest in Python, Tableau & Machine learning Experience/interest in building machine learning systems using big data Experience/interest in data visualization and presentation Knowledge of US/UK/Indian/Middle-East Healthcare system, Specially Fraud management Certifications - Technical SAS, Python, Spark; Healthcare domain - AHM

Role Description Model Risk Managements mission is to manage, independently and actively, model risk globally in line with the bank's risk appetite with responsibility for: Performing robust independent model validation; Ensuring early and proactive identification of Model Risks; Effectively managing and mitigating Model Risks; Establishing Model Risk metrics; Designing and implementing a strong Model Risk Management and governance framework; Supporting bank-wide Model Risk-related policies. This role spans all aspects of validation applicable to the portfolio of estimation approaches within the Deutsche Bank Combined US Operations (CUSO) across all relevant business units and risk types. Your key responsibilities The core responsibility will be to validate Stress testing models used within the larger CCAR PPNR umbrella for DB USA. Its important for incumbent to grasp and understand the different business including Investment Banking, Private Bank, Corporate Bank and Asset Management. However, the role might necessitate model validator to be flexible in moving around different risk areas within US model validation team outside of core area of responsibility. Key tasks include, but not limited to model performance testing, scenario analysis, sensitivity analysis, and conceptual assessment of model assumptions/limitations/weaknesses. Developing challenger models including independent data collection and by performing complex analysis and testing. Follow regulatory guidelines and the Banks policies and procedures for model risk management, especially CCAR-specific guidelines. Bringing efficiency by automating processes and uplifting frameworks utilized in validation activities. Your skills and experience 6-10 years of professional experience in model development/ validation or related areas. 2-3 years of experience in PPNR model development / validation. Previous experience in stress testing (DFAST/CCAR/ICAAP) would be a plus. The candidate must possess substantial knowledge and experience in working with B/PPNR models across various lines of business, including Corporate Banking, Private Banking, Investment Banking, and Treasury Functions. Ability to analyse and understand financial statements (Balance sheet, Income statement) will be advantageous. Experience and knowledge of Statistical techniques, strong analytical skills with experience in relevant software packages, e.g., R and Python. Candidate needs to have above average report drafting skills and should be able to independently compile model validation reports, follow-through on mitigation of validation findings, and documentation thereof. Good presentation & communication skills. Ability to deal with stakeholders and handle difficult conversations. Candidates with Mathematics/Statistics/Economics/Engineering/ MBA or allied background holding Graduate/Post-Graduate degrees are preferred. CFA / FRM certification will be a plus for the role. Candidates having experience / strong knowledge in Business Intelligence tools like Power BI, Tableau, Automation through MS-Access / VBA, developing framework, designing presentations will be a plus for the role.

Title and Summary Economic Analyst, North America (NAM)Economic Analyst, North America (NAM) Overview The Mastercard Economics Institute (MEI) is an economics lab powering scale at Mastercard by owning economic thought leadership in support of Mastercards efforts to build a more inclusive and sustainable digital economy The Economics Institute was launched in 2020 to analyze economic trends through the lens of the consumer to deliver tailored and actionable insights on economic issues for customers, partners and policymakers The Institute is composed of a team of economists and data scientists that utilize & synthesize the anonymized and aggregated data from the Mastercard network together with public data to bring powerful insights to life, in the form of 1:1 presentation, global thought leadership, media participation, and commercial work through the companys product suites About the Role We are looking for an economic analyst to engage in data analytics and economic research for U.S. and Canada. This individual will report to the VP, Lead Economist for North America at MEI, and will have the following responsibilities: Support client and stakeholder engagements for the Economics Institute, specifically focusing on NAM economic research. Support collaboration with external clients, academic institutions, and industry partners. Generate initial insights to help create effective, impactful, and quality-assured storylines and visuals at the stream or small project level. Synthesize analyses into clear, sound recommendations. Outline and help write reports and draft client presentations at the work stream or project level. Enhance existing products and partner with internal stakeholders to create new solutions. Proactively seek new knowledge and structure project work to facilitate the capture of intellectual capital with minimal oversight. Actively participate in new solution development and support thought leadership activities by building knowledge, know-how, and best practices related to economic research; share and leverage to continuously improve quality and productivity. All About You Required: Bachelor's degree in Economics (preferred), Statistics, or Mathematics. Experience in statistical modeling, quantitative analysis, data engineering, R development, with a focus economic research. Understanding of statistics and econometric concepts, modeling and forecasting techniques Proficiency in SQL and Hadoop is essential. Expertise in R, Python, or other major statistical packages is essential. Experience with Tableau is strongly preferred. Knowledge of JavaScript for data visualization is a plus. Proficient in key econometric and statistical techniques such as predictive modeling, logistic regression, survival analysis, time series modeling, design of experiments, decision trees, and data mining methods. Willingness to learn additional statistical applications or software as required. Experience in the financial services industry is desirable. Excellent communication and strong writing skills required.

We are looking for passionate and talented professionals, who share our vision for data-driven marketing products to join us and take a leading role in shaping the growth of our team. Job Summary We are seeking a results-oriented Marketing Analytics Lead with 68 years of experience in data analytics, statistical modelling, and marketing insights. The ideal candidate is confident in owning complex analyses of A/B testing and portfolio optimization and can comfortably engage with senior stakeholders. Experience in financial services, banking, or payments is strongly preferred. Exposure to GenAI in marketing analytics will be an added advantage. Key Responsibilities Lead design and execution of A/B tests, campaign analytics, and test-control methodologies. Perform deep-dive analysis on customer journeys, marketing funnels, and portfolio performance. Develop predictive models to inform segmentation, personalization, and targeting strategies. Provide thought leadership in marketing measurement and performance optimization. Translate insights into business impact through crisp storytelling and stakeholder engagement. Mentor junior analysts and contribute to best practices in analytics delivery. Partner with marketing, finance, and data engineering to ensure robust data solutions. Basic qualifications Undergraduate degree with 6-8 years of analytical experience in consulting, analytics, or data science with a strong focus on marketing analytics. Deep knowledge of business KPIs, financials and organizational leadership Proficiency in tools such as SQL, Python, R, or SAS. Strong foundation in A/B testing, test-control analysis, and statistical modelling. Experience generating new knowledge or creating innovative solutions for a firm Proven ability to communicate insights effectively with clarity and executive presence. Experience with data visualization platforms (e.g., Tableau, Power BI). Analytical, interpretive, and problem-solving skills, including the proven ability to analyze large amounts of data and synthesize key findings and recommendations Logical, structured thinking and affinity for statistical and numerical analysis Advanced Word, Excel, and PowerPoint skills Ability to manage multiple tasks and clients in a fast-paced, deadline-driven environment Eligibility to work in the country where you are applying, as well as apply for travel visas as required by travel needs Preferred Qualifications Background in banking, payments, or financial institutions. Experience working on digital marketing, lifecycle campaigns, or customer analytics. Exposure to or hands-on use of GenAI tools for marketing insight generation or automation. Masters degree in Data Science, Statistics, Econometrics, Marketing, or related field is a plus.

About the Role We are seeking a Data Scientist with strong expertise in Python and SQL to join our growing data team. Youll work on data modeling, predictive analytics, and business intelligence projects that directly impact strategic decision-making. Key Responsibilities Extract, clean, and transform data from multiple sources using SQL and Python. Build predictive models and machine learning algorithms for business use cases. Perform exploratory data analysis (EDA) and generate actionable insights. Create interactive dashboards & reports (Power BI/Tableau). Optimize and maintain data pipelines, ETL processes, and workflows . Collaborate with cross-functional teams to translate business needs into analytical solutions. Present analytical results in a clear, visual, and business-friendly format. Required Skills 1–5 years of experience in Data Science or Data Analytics roles. Strong proficiency in Python (NumPy, Pandas, Scikit-learn, Matplotlib, Seaborn). Advanced SQL skills (complex queries, joins, window functions, optimization). Understanding of machine learning algorithms and statistical methods. Experience in data visualization tools (Power BI, Tableau, or similar). Strong problem-solving and analytical skills. Bachelor’s/Master’s in Computer Science, Data Science, Statistics, Mathematics, or related fields. Nice to Have Familiarity with cloud platforms (AWS, Azure, GCP). Exposure to Big Data tools (Spark, Hadoop). Basic understanding of APIs and automation scripts . What We Offer Competitive industry-standard salary + performance incentives. Flexible working hours & hybrid/remote opportunities. Exposure to real-world, high-impact projects .

Role Summary/Purpose: The AVP,/VP Remediation Reporting Insight Analyst drives maturity in our remediation performance capabilities. This role will be responsible for ongoing remediation reporting, and for analysis leveraging remediation and issue management data to identify critical insights, patterns, and trends relevant to process performance, health drivers, KPI, KRI reporting, Compliance and other governance reporting requirements. Essential Responsibilities: Prepare and analyze ongoing remediation reporting, identifying trends and/or anomalies warranting additional research. Oversee ongoing reporting and deep dive analysis into KPIs and KRIs. Establish mechanisms and technical queries to combine available data, and conduct detailed analysis to identify opportunities for process enhancements, early warning triggers, and health drivers Engage with Issue Management teams to support opportunities for improvements and consistent reporting/monitoring across the teams. Oversee and ensure compliance with model and non-model governance requirements for the full lifecycle of applicable tools. Develop presentations synthesizing analysis for reporting to both internal and regulatory audiences. Lead projects for reporting development and data integration. Provide process focused analytics support to remediation and related process stakeholders. Analyze all aspects of the remediation experience by developing indices using additional variables, including but not limited to, remediation volume, key drivers, and similar. Required Skills/Knowledge: Bachelor's degree and a minimum of 8+ years of hands-on reporting and analytics experience OR in lieu of a Bachelor's Degree, a High School Diploma / GED and a minimum of 10+ years of hands-on reporting and analytics experience Minimum 2 years experience utilizing statistical techniques, e.g., modeling, A/B testing, and segmentation. 3+ years of experience with proven ability to extract unstructured and structured data with strong programming ability in SAS, SQL, R, Python or other programming language. Desired Characteristics: Bachelor's degree, preferably in a quantitative discipline, such as statistics, mathematics, or engineering. Strong project management, communications, multi-tasking, ability to work independently, relationship management skills are keys to success. Solid understanding of card industry financial P&L drivers and key sensitivities, with business performance reporting experience. Demonstrated ability to manage complexity and multiple initiatives. Ability to perform ad-hoc analysis, glean and form business insights under aggressive timelines. Results-oriented; ready to challenge the status quo for continuous improvement. Eligibility Criteria: Bachelor's degree and a minimum of 8+ years of hands-on reporting and analytics experience OR in lieu of a Bachelor's Degree, a High School Diploma / GED and a minimum of 10+ years of hands-on reporting and analytics experience

We are looking for a seasoned Machine Learning Operations (MLOps) Engineer to build and optimize machine learning platforms. This role requires deep expertise in machine learning engineering and infrastructure, with a strong focus on developing scalable inference systems. Proven experience in building and deploying ML platforms in production environments is essential. This remote position also requires excellent communication skills and the ability to independently tackle complex challenges with innovative solutions. If you get a thrill working with cutting-edge technology and love to help solve customers problems, wed love to hear from you. Its time to rethink the possible. Are you ready? What you will be doing: Build and optimize ML Platforms to support cutting-edge machine learning and deep learning models. Collaborate closely with cross-functional teams to translate business objectives into scalable engineering solutions. Develop CI/CD workflows for ML models and data pipelines using tools like Cloud Build, GitHub Actions, or Jenkins. Automate model training, validation, and deployment across development, staging, and production environments. Monitor and maintain ML models in production using Vertex AI Model Monitoring, logging (Cloud Logging), and performance metrics. Ensure reproducibility and traceability of experiments using ML metadata tracking tools like Vertex AI Experiments or MLflow. Manage model versioning and rollbacks using Vertex AI Model Registry or custom model management solutions. Collaborate with data scientists and software engineers to translate model requirements into robust and scalable ML systems. Optimize model inference infrastructure for latency, throughput, and cost efficiency using GCP services such as Cloud Run, Kubernetes Engine (GKE), or custom serving frameworks. Implement data and model governance policies , including auditability, security, and access control using IAM and Cloud DLP. Stay current with evolving GCP MLOps practices , tools, and frameworks to continuously improve system reliability and automation Qualifications and skills: Bachelor's degree in computer science, Information Technology, or a related field. 3+ years of relevant industry experience. Proven track record in designing and implementing cost-effective, scalable machine learning inference systems. Hands-on experience with leading deep learning frameworks such as TensorFlow, PyTorch, Hugging Face, and LangChain. Proven experience in implementing MLOps solutions on Google Cloud Platform (GCP) using services such as Vertex AI , Cloud Storage , BigQuery , Cloud Functions , and Dataflow . Solid understanding of machine learning algorithms, natural language processing (NLP), and statistical modeling. Solid understanding of core computer science concepts, including algorithms, distributed systems, data structures, and database management. Strong problem-solving skills, with the ability to tackle complex challenges using critical thinking and propose innovative solutions. Effective in remote work environments, with excellent written and verbal communication skills. Proven ability to collaborate with team members and stakeholders to ensure clear understanding of technical requirements and project goals. Expertise in public cloud platforms, particularly Google Cloud Platform (GCP) and Vertex AI. Proven experience in building and scaling agentic AI systems in production environments. In-depth understanding of large language model (LLM) architectures, parameter scaling, optimization strategies and deployment trade-offs.

Roles & Responsibilities: Ensure that high quality bio statistical and psychopharmacology support is provided by the Analytics team Ensure that staff implement innovative, rigorous bio statistical methods to meet study objectives Lead RWE (Real World Evidence) large scale analytics (LSA) studies. Run statistical programs in R, R shiny, deploy study packages and generate reliable RWE results in TFLs with minimal supervision. Provide statistical support for design, implementation, running, analysis and dissemination of results for clinical trials Design and analyze clinical research projects Create and execute Statistical Analysis Plans Strong Knowledge in RWE(Real World Evidence) with Bio statistics Background Experience in creating cohort analysis or Meta analysis or Survival analysis or Bayesian Versus Frequentest Approaches to Clinical Trials Experience in implementing generalized mixture models, Bayesian mixer models, Fixed-effects and Random-effects models Knowledge on Statistical Process Control, Stochastic Optimization Knowledgeable in R or Python programming Skills and shiny web app development Knowledge on Cloud platform like AWS Exposure to Healthcare data formats like HL7, OMOP, ODHSI Exposure to RWE, RWA, RWD Experience with data sources like registries, EMR Good communications Skills

We are looking for a seasoned Machine Learning Operations (MLOps) Architect to design, build, and optimize machine learning platforms. This role requires deep expertise in machine learning engineering and infrastructure, with a strong focus on developing scalable inference systems. Proven experience in building and deploying ML platforms in production environments is essential. This remote position also requires excellent communication skills and the ability to independently tackle complex challenges with innovative solutions. If you get a thrill working with cutting-edge technology and love to help solve customers problems, wed love to hear from you. Its time to rethink the possible. Are you ready? What you will be doing Architect and optimize ML Platforms to support cutting-edge machine learning and deep learning models. Collaborate closely with cross-functional teams to translate business objectives into scalable engineering solutions. Lead the end-to-end development and operation of high-performance, cost-effective inference systems for a diverse range of models, including state-of-the-art large language models (LLMs). Provide technical leadership and mentorship to cultivate a high-performing engineering team. Develop CI/CD workflows for ML models and data pipelines using tools like Cloud Build, GitHub Actions, or Jenkins. Automate model training, validation, and deployment across development, staging, and production environments. Monitor and maintain ML models in production using Vertex AI Model Monitoring, logging (Cloud Logging), and performance metrics. Ensure reproducibility and traceability of experiments using ML metadata tracking tools like Vertex AI Experiments or MLflow. Manage model versioning and rollbacks using Vertex AI Model Registry or custom model management solutions. Collaborate with data scientists and software engineers to translate model requirements into robust and scalable ML systems. Optimize model inference infrastructure for latency, throughput, and cost efficiency using GCP services such as Cloud Run, Kubernetes Engine (GKE), or custom serving frameworks. Implement data and model governance policies , including auditability, security, and access control using IAM and Cloud DLP. Stay current with evolving GCP MLOps practices , tools, and frameworks to continuously improve system reliability and automation. Qualifications & Skills Bachelor's degree in computer science, Information Technology, or a related field. 5+ years of relevant industry experience. Proven track record in designing and implementing cost-effective, scalable machine learning inference systems. Hands-on experience with leading deep learning frameworks such as TensorFlow, PyTorch, Hugging Face, and LangChain. Proven experience in implementing MLOps solutions on Google Cloud Platform (GCP) using services such as Vertex AI , Cloud Storage , BigQuery , Cloud Functions , and Dataflow . Solid understanding of machine learning algorithms, natural language processing (NLP), and statistical modeling. Solid understanding of core computer science concepts, including algorithms, distributed systems, data structures, and database management. Strong problem-solving skills, with the ability to tackle complex challenges using critical thinking and propose innovative solutions. Effective in remote work environments, with excellent written and verbal communication skills. Proven ability to collaborate with team members and stakeholders to ensure clear understanding of technical requirements and project goals. Expertise in public cloud platforms, particularly Google Cloud Platform (GCP) and Vertex AI. Proven experience in building and scaling agentic AI systems in production environments. In-depth understanding of large language model (LLM) architectures, parameter scaling, optimization strategies and deployment trade-offs.

Roles and Responsibility Analyze ecommerce data to identify trends and patterns, providing insights to stakeholders. Develop and implement analytics solutions to optimize business operations and improve performance. Collaborate with cross-functional teams to design and execute marketing campaigns. Monitor and report on key performance indicators (KPIs) to measure campaign success. Identify opportunities for process improvements and recommend changes. Stay updated with industry trends and emerging technologies in ecommerce analytics. Job Requirements Strong understanding of ecommerce platforms and their applications. Experience with data analysis tools and techniques, such as statistical modeling and machine learning. Excellent communication and problem-solving skills, with the ability to work effectively in a team environment. Ability to interpret complex data sets and provide actionable recommendations. Strong analytical mindset with attention to detail and organizational skills. Familiarity with industry-specific regulations and standards.

Welcome to the relentless pursuit of better. Inviting applications for the role of Data Scientist The position is based out of India and the focus of the role is to have enterprise level experience in Predictive and NLP Model build, validation, implementation, monitoring, etc. and do analysis on data, be able to understand, translate and integrate the analysis. We are seeking a highly skilled and experienced Generative AI Specialist for developing and implementing cutting-edge generative models to solve complex problems using LLM technology. Need to collaborate with cross-functional teams, conduct research, and deliver innovative solutions in the field of generative artificial intelligence. Responsibilities Participating and collaborating with operation teams in the organization to understand the business requirements and to deliver scalable solutions. Conduct thorough research on state-of-the-art generative AI techniques, stay up to date with the latest advancements, and apply them to enhance the capabilities of LLM models. Ability to create models using Classification and Regression techniques and perform Hypothesis Testing and Feature selection. Strong analytical and problem-solving skills, and ability to set goals and meet deadlines in fast paced working environment. Analyze user behavior, conversion data, customer journeys to generate hypothesis and build optimization plans and provide insights for feature improvements. Perform deep dive analyses on key business trends from different perspectives and package the insights into easily consumable presentations and documents. Lead efforts to train and fine-tune language models, ensuring they meet high standards of performance, efficiency, and safety. Work on strategies to scale language models, optimizing for efficiency and reducing resource consumption. Deploy model in cloud- Azure, AWS, GCP. Qualifications we seek in you. Minimum qualifications Education in Statistics, Mathematics, Computer Science, or another quantitative field. Preferred qualifications Experience using computer languages (Python, SQL, etc.) to manipulate data and draw insights from large data sets. Experience in deploying LLM models in production. Experience in using industry standard AI/ML libraries i.e., Sklearn, Keras, Tensorflow, AutoML etc. Solid understanding of generative AI concepts, frameworks, and techniques, with hands-on experience in developing and deploying generative models. Proficiency in working with Large Language Models (LLMs), such as GPT-3, GPT-4, or similar models like Llama 2, Falcon LLM. Strong programming skills in languages such as Python and experience with deep learning libraries/frameworks (e.g., TensorFlow, PyTorch). Strong communication and collaboration skills, with the ability to work effectively in a multidisciplinary team environment. Familiarity with natural language processing (NLP) and understanding of various NLP tasks is a plus. Prior experience in handling LLM use cases or working with large-scale language models is highly desirable. Ensure data quality and integrity through best practices and compliance to framework, architecture, and coding standards. Genpact is an Equal Opportunity Employer and considers applicants for all positions without regard to race, color, religion or belief, sex, age, national origin, citizenship status, marital status, military/veteran status, genetic information, sexual orientation, gender identity, physical or mental disability or any other characteristic protected by applicable laws. Genpact is committed to creating a dynamic work environment that values diversity and inclusion, respect and integrity, customer focus, and innovation. For more information, visit www.genpact.com. Follow us on Twitter, Facebook, LinkedIn, and YouTube. Furthermore, please do note that Genpact does not charge fees to process job applications and applicants are not required to pay to participate in our hiring process in any other way. Examples of such scams include purchasing a 'starter kit,' paying to apply, or purchasing equipment or training.

Location - All Genpact Locations Responsibilities Professional experience with different regression and classification methods in implementation and deployment of project on AWS GCP and Azure cloud platform. Follow the standard practice and guidelines while using Python, SQL. Experience with Langchain framework for GenAI. Develop and fine-tuning Generative AI models such as GPT for various applications. Using Generative AI to work on tasks like text generation, sentiment analysis, chatbots and language translation using RAG and agent-based models. Adjust language models that have already been trained for generative AI applications. Experience in tokenization and embeddings and must have used GPT, LLaMA, Huggingface, Mistral, AWS BedRock for deploying the models. Analyze data and Generating insights using generative AI techniques for predictive modelling and data generation. Building chatbot using different scalable data source for generating charts and statement. Having experience building front end application using Streamlit/Gradio/Flask/Fast for Generative AI input and output display. Responsible for weekly release of upgrades and new features to enhance current algorithm. Evaluating the performance of generative AI models and implementing improvements based on feedback. Ensuring ethical and responsible use of AI by addressing bias, privacy concerns and fairness in AI models. Must Demonstrate understanding of evaluation metrics specific to GenAI task such as inception score, frechet inception distance, perpetual path length. Collaborating with cross-functional teams, including data scientist, engineers, and domain experts to integrate Generative AI into product or services. Able to design Machine learning, Deep learning and Generative AI architecture and its successful execution in the project. Must have basic understanding on Word and Excel. Proficiency in programming language like Python, SQL, frameworks such as Langchain for AI model development. Experience on Rest API, Flask API, Fast API. Qualifications we seek in you!Minimum Qualifications / Skills Any Graduate BE/B- Tech, BCA, MCA, BSc/MSc Behavioral / team skills Personal drive and positive work ethic to deliver results within tight deadlines and in demanding situations Flexibility to adapt to a variety of engagement types, working hours and work environments and locations Excellent written, oral communication and presentation skills Bring a data-driven approach to decision making intellectually curious, always eager to learn new skills and share the knowledge with others Proactive planner and can work independently to manage own responsibilities Genpact is an Equal Opportunity Employer and considers applicants for all positions without regard to race, color, religion or belief, sex, age, national origin, citizenship status, marital status, military/veteran status, genetic information, sexual orientation, gender identity, physical or mental disability or any other characteristic protected by applicable laws. Genpact is committed to creating a dynamic work environment that values diversity and inclusion, respect and integrity, customer focus, and innovation. Get to know us at genpact.com and on LinkedIn, X, YouTube, and Facebook.Furthermore, please do note that Genpact does not charge fees to process job applications and applicants are not required to pay to participate in our hiring process in any other way. Examples of such scams include purchasing a 'starter kit,' paying to apply, or purchasing equipment or training.

Ready to build the future with AI? At Genpact, we dont just keep up with technologywe set the pace. AI and digital innovation are redefining industries, and were leading the charge. Genpacts AI Gigafactory, our industry-first accelerator, is an example of how were scaling advanced technology solutions to help global enterprises work smarter, grow faster, and transform at scale. From large-scale models to agentic AI, our breakthrough solutions tackle companies most complex challenges. If you thrive in a fast-moving, innovation-driven environment, love building and deploying cutting-edge AI solutions, and want to push the boundaries of whats possible, this is your moment. Genpact (NYSE: G) is an advanced technology services and solutions company that delivers lasting value for leading enterprises globally. Through our deep business knowledge, operational excellence, and cutting-edge solutions – we help companies across industries get ahead and stay ahead. Powered by curiosity, courage, and innovation , our teams implement data, technology, and AI to create tomorrow, today. Get to know us at genpact.com and on LinkedIn, X, YouTube, and Facebook. Inviting applications for the role of Lead Consultant-Data Scientists with AI and Generative Model experience! We are currently looking for a talented and experienced Data Scientist with a strong background in AI, specifically in building generative AI models using large language models, to join our team. This individual will play a crucial role in developing and implementing data-driven solutions, AI-powered applications, and generative models that will help us stay ahead of the competition and achieve our ambitious goals. Responsibilities • Collaborate with cross-functional teams to identify, analyze, and interpret complex datasets to develop actionable insights and drive data-driven decision-making. • Design, develop, and implement advanced statistical models, machine learning algorithms, AI applications, and generative models using large language models such as GPT-3, BERT and also frameworks like RAG, Knowledge Graphs etc. Communicate findings and insights to both technical and non-technical stakeholders through clear and concise presentations, reports, and visualizations. Continuously monitor and assess the performance of AI models, generative models, and data-driven solutions, refining and optimizing them as needed. Stay up-to-date with the latest industry trends, tools, and technologies in data science, AI, and generative models, and apply this knowledge to improve existing solutions and develop new ones. Mentor and guide junior team members, helping to develop their skills and contribute to their professional growth. Qualifications we seek in you: Minimum Qualifications • Bachelor's or Master's degree in Data Science, Computer Science, Statistics, or a related field. Experience in data science, machine learning, AI applications, and generative AI modelling. Strong expertise in Python, R, or other programming languages commonly used in data science and AI, with experience in implementing large language models and generative AI frameworks. Proficient in statistical modelling, machine learning techniques, AI algorithms, and generative model development using large language models such as GPT-3, BERT, or similar frameworks like RAG, Knowledge Graphs etc. Experience working with large datasets and using various data storage and processing technologies such as SQL, NoSQL, Hadoop, and Spark. Strong analytical, problem-solving, and critical thinking skills, with the ability to draw insights from complex data and develop actionable recommendations. Excellent communication and collaboration skills, with the ability to work effectively with cross-functional teams and explain complex concepts to non-technical stakeholders. Preferred Qualifications/ skills • Experience in deploying AI models, generative models, and applications in a production environment using cloud platforms such as AWS, Azure, or GCP. Knowledge of industry-specific data sources, challenges, and opportunities relevant to Insurance Demonstrated experience in leading data science projects from inception to completion, including project management and team collaboration skills. Why join Genpact? Lead AI-first transformation – Build and scale AI solutions that redefine industries Make an impact – Drive change for global enterprises and solve business challenges that matter Accelerate your career —Gain hands-on experience, world-class training, mentorship, and AI certifications to advance your skills Grow with the best – Learn from top engineers, data scientists, and AI experts in a dynamic, fast-moving workplace Committed to ethical AI – Work in an environment where governance, transparency, and security are at the core of everything we build Thrive in a values-driven culture – Our courage, curiosity, and incisiveness - built on a foundation of integrity and inclusion - allow your ideas to fuel progress Come join the 140,000+ coders, tech shapers, and growth makers at Genpact and take your career in the only direction that matters: Up. Let’s build tomorrow together. Genpact is an Equal Opportunity Employer and considers applicants for all positions without regard to race, color, religion or belief, sex, age, national origin, citizenship status, marital status, military/veteran status, genetic information, sexual orientation, gender identity, physical or mental disability or any other characteristic protected by applicable laws. Genpact is committed to creating a dynamic work environment that values respect and integrity, customer focus, and innovation. Furthermore, please do note that Genpact does not charge fees to process job applications and applicants are not required to pay to participate in our hiring process in any other way. Examples of such scams include purchasing a 'starter kit,' paying to apply, or purchasing equipment or training.

Position : Data Science Trainer Salary : As per company standards Experience : 1yr- 5yrs WORK FROM OFFICE MANDATORY (Full time, permanent) Notice Period : immediate Location : Pune Job Description : Candidates must have the ability to take both theory and practical sessions. Should have excellent knowledge on Python Data Science technologies. Should be able to teach Machine learning, deep learning, artificial Intelligence, SQL, Django .Able to resolve students' queries. We expect good communication and presentation skills. Able to explain complex subjects in a clear and interesting way. Dynamic personality. Should be flexible to conduct Weekend Batches as well as Weekday Batches. Responsibilities and Duties - Devise technical training programs according to organizational requirements. Produce training schedules and classroom agenda. Determine course content according to objectives. Prepare training material (presentations, worksheets etc.) Execute training sessions Keep and report data on completed courses, absences, issues etc. Observe and evaluate results of training programs. Determine overall effectiveness of programs and make improvements. (Note: No part time , No work from home) Interested candidates can drop their CV on aishwaryapawar@sevenmentor.com OR contact on 9503389804

Job Purpose Looking for exceptional Data Scientist with a proven track record of experience in Predictive analytics. Job Responsibilities(JR) : 6 8 Areas Actionable (4-6) Scorecard Building and Modelling Developing analytical models to assess risk profile of a customer / identifying cross-sell opportunities/fraud control for new and existing customers Responsible for development and deployment of various scorecards / models for the credit risk / Retail asset products of the Bank within the specified timelines. Ensure the deployment also is line with Bank’s strategies so as to gain maximum efficiencies. Estimate probability of default arising out of the scorecards and monitor deviation from expected default rates. Monitor portfolio and identify pockets of opportunity for business growth and risk alerts to control NPAs. Communicate these alerts to the respective owners and follow-up for closure Formulating data cuts and strategies to assess credit risk for new and existing customers of the Bank. Give feedback to stakeholders to improve the usage of the models Develop novel approaches/algorithms in Risk modeling to constantly improve the operational efficacy of current models and its impact to stake holders To adopt the latest trends wrt fintech companies by applying the best-in-class financial models, risk strategies To work on various aspects related to automation of scorecards in Analytics domain. Explore data available within the Banks ecosystem but not used currently to meet the above stated business objectives Innovation Thinking, evolving and making significant changes in the processes, techniques, methods so as to save time, energy and money. Any other assignments depending on the needs of the organization Educational Qualifications Key Skills 1. MCA/MTech/MSc Statistics or Economics/BTech/MBA or equivalent in Computer science/Statistics or related areas with strong inclination towards machine learning algorithms is preferred Excellent problem solving capabilities with strong fundamentals in computer science Strong technical & analytical skills Hands-on experience in data wrangling (ETL), feature engineering, building and deploying scalable machine learning algorithms Strong written and verbal communication skills Excellent knowledge of current trends in the field of machine learning/analytics field Experience Required Experience of 2+ years in analytics/predictive modeling/machine learning Experience of 2+ years in Python/R in building as well as deploying scalable analytics based models Exposure to banking preferable Major Stakeholders (intra team and cross functional stakeholders, who would need to be interacted with for discharging duties) Credit Policy Underwriting Process Fraud Control Product Credit Bureaus Third Party Analytics Service Providers IT Legal Information Security

Data Science Senior Advisor Data Science is all about breaking new ground to enable businesses to answer their most urgent questions. Pioneering massively parallel data-intensive analytic processing, our mission is to develop a whole new approach to generating meaning and value from petabyte-scale data sets and shape brand new methodologies, tools, statistical methods and models. Whats more, we are in collaboration with leading academics, industry experts and highly skilled engineers to equip our customers to generate sophisticated new insights from the biggest of big data. Join us to do the best work of your career and make a profound social impact as a Data Science Senior Advisor on our Pricing Analytics Team under Client Solutions Group located in Bangalore . What youll achieve As a Data Science Senior Advisor, you will be responsible for contributing to business strategy and influence decision making based on information gained from deep dive analysis. You will produce actionable and compelling recommendations by interpreting insights from complex data sets. You will design processes to consolidate and examine unstructured data to generate actionable insights. You will also partner with business leaders, engineers and industry experts to construct predictive models, algorithms and probability engines. You will: •Collaborate with internal and external teams to understand customer requirements •Develop and apply a broad range of techniques and theories from statistics, machine learning, and business intelligence to deliver actionable business insights •Develop and drive testing of algorithms efficacy for differing analytical use-cases •Performs end-to-end steps involved in model development while establishing subject-matter expertise •Work with the academic and business community to develop new techniques and to contribute to research in the area of large databases Take the first step towards your dream career Every Dell Technologies team member brings something unique to the table. Here’s what we are looking for with this role: Essential Requirements •8 to 12 years of related experience •Solid statistical skills. ML exp, LLM models •Solid Python Programming •Good understanding of business environment and industry trends •Good communication and problem-solving skills and being customer focused Desirable Requirements •Bachelor’s degree •Ability to act as a coach to the team •Strong product/technology/industry knowledge

Job Title: Data Scientist Experience: 5+ years Location: Ambattur Estate, Chennai Work Type : Work from office (no hybrid or remote) Email to Apply: jerlinbetsy.m@accesshealthcare.com About the Role: Access Healthcare is looking for a talented and driven Data Scientist to turn complex data into actionable business insights. If you have strong technical expertise, a knack for problem-solving, and the ability to communicate stories through data, this is your opportunity to make a real business impact. Eligibility Criteria : 5+ years of experience, with a track record of solving complex business problems using data. Certifications in Data Science, Machine Learning, or AI platforms ( preferred) Competency Requirement (Technical & Behavioral): Proficiency in Python or R for data analysis and model building. Strong knowledge of SQL for data extraction and manipulation. Experience with machine learning algorithms (regression, classification, clustering, etc.) Familiarity with data visualization tools like Tableau, Power BI Strong analytical and problem-solving skills Excellent communication and storytelling abilities to present complex data in a clear and concise manner Ability to work both independently and collaboratively in cross-functional teams Capacity to handle change, stay open to different ideas, support positive changes. Very high in Integrity and should be attentive to detail. Should be self- motivated and agile Should be able to influence and inspire Teams at all levels of the organization Roles & Responsibilities: Work closely with business, product, BEX & SQ teams to understand requirements Gather structured and unstructured data from multiple sources Clean and transform data to ensure quality and consistency Perform statistical analysis to identify trends, correlations, and anomalies. Use visualization tools to communicate data patterns and insights Design, build, and validate predictive models wherever required Select appropriate techniques based on problem type for ex regression Translate complex data findings into actionable business insights Develop reports, and visualizations to communicate results effectively to non-technical stakeholders Design and run experiments to test hypotheses and measure the impact of business decisions. Analyze test results and suggest next steps or optimizations. Stay updated with the latest trends, tools, and technologies in data science and machine learning. Contact ID - jerlinbetsy.m@accesshealthcare.com

Experience in CI/CD pipelines, scripting languages, and a deep understanding of version control systems (e.g. Git), containerization (e.g. Docker), and continuous integration/deployment tools (e.g. Jenkins) third party integration is a plus, cloud computing platforms (e.g. AWS, GCP, Azure), Kubernetes and Kafka. Experience in 4+ years of experience building production-grade ML pipelines. Proficient in Python and frameworks like Tensorflow, Keras, or PyTorch. Experience with cloud build, deployment, and orchestration tools Experience with MLOps tools such as MLFlow, Kubeflow, Weights & Biases, AWS Sagemaker, Vertex AI, DVC, Airflow, Prefect, etc., Experience in statistical modeling, machine learning, data mining, and unstructured data analytics. Understanding of ML Lifecycle, MLOps & Hands on experience to Productionize the ML Model Detail-oriented, with the ability to work both independently and collaboratively. Ability to work successfully with multi-functional teams, principals, and architects, across organizational boundaries and geographies. Equal comfort driving low-level technical implementation and high-level architecture evolution Experience working with data engineering pipelines.