170 Linear Regression Jobs

Project Role : Responsible AI Engineer Project Role Description : Assess AI systems for adherence to predefined thresholds and benchmarks related to responsible, ethical and sustainable practices. Design and implement technology mitigation strategies for systems to ensure ethical and responsible standards are achieved. Must have skills : Responsible AI Good to have skills : NAMinimum 15 year(s) of experience is required Educational Qualification : 15 years full time education Summary :As a Responsible AI Engineer, you will assess AI systems for adherence to predefined thresholds and benchmarks related to responsible, ethical, and sustainable practices. Design and implement technology mitigation strategies for systems to ensure ethical and responsible standards are achieved. Roles & Responsibilities:- Expected to be a SME with deep knowledge and experience.- Should have Influencing and Advisory skills.- Responsible for team decisions.- Engage with multiple teams and contribute on key decisions.- Expected to provide solutions to problems that apply across multiple teams.- Develop and implement responsible AI frameworks.- Conduct audits and assessments of AI systems for ethical compliance.- Collaborate with cross-functional teams to ensure responsible AI practices are integrated. Professional & Technical Skills: - Must To Have Skills: Proficiency in Responsible AI.- Strong understanding of statistical analysis and machine learning algorithms.- Experience with data visualization tools such as Tableau or Power BI.- Hands-on implementing various machine learning algorithms such as linear regression, logistic regression, decision trees, and clustering algorithms.- Solid grasp of data munging techniques, including data cleaning, transformation, and normalization to ensure data quality and integrity. Additional Information:- The candidate should have a minimum of 15 years of experience in Responsible AI.- This position is based at our Bengaluru office.- A 15 years full-time education is required. Qualification 15 years full time education

Management Level :07- I&F Decision Sci Practitioner Manager Location :Mumbai Must-have skills :Risk Analytics, Model Development, Validation, and Auditing, Performance Evaluation, Monitoring, Governance, Statistical Techniques:Linear Regression, Logistic Regression, GLM, GBM, XGBoost, CatBoost, Neural Networks, Programming Languages:SAS, R, Python, Spark, Scala, Tools:Tableau, QlikView, PowerBI, SAS VA, Regulatory Knowledge:Basel/CCAR/DFAST/CECL/IFRS9, Risk Reporting and Dashboard Solutions Good to have skills :Advanced Data Science Techniques, AML, Operational Risk Modelling, Cloud Platform Experience (AWS/Azure/GCP), Machine Learning Interpretability and Bias Algorithms Job Summary We are seeking a highly skilled I&F Decision Sci Practitioner Manager to join the Accenture Strategy & Consulting team in the Global Network Data & AI practice. You will be responsible for leading risk model development, validation, and auditing activities, ensuring performance evaluation, monitoring, governance, and documentation. This role also provides opportunities to work with top financial clients globally, utilizing cutting-edge technologies to drive business capabilities and foster innovation. Roles & Responsibilities: Engagement Execution Lead the team in the development, validation, governance, strategy, transformation, implementation, and end-to-end delivery of risk solutions for clients. Manage workstreams for large and small projects, overseeing the quality of deliverables for junior team members. Develop and frame Proof of Concept for key clients where applicable. Practice Enablement Mentor, guide, and counsel analysts and consultants. Support the development of the practice by driving innovations and initiatives. Support efforts of sales team to identify and win potential opportunities by assisting with RFPs, RFI. Assist in designing POVs, GTM collateral. Professional & Technical Skills: 7-12 years of relevant Risk Analytics experience at one or more Financial Services firms or Professional Services / Risk Advisory with significant exposure to Credit Risk :PD/LGD/EAD Models, CCAR/DFAST Loss Forecasting, Revenue Forecasting Models, IFRS9/CECL Loss Forecasting across Retail and Commercial portfolios. Credit Acquisition/Behavior :Modeling, Credit Policies, Limit Management, Acquisition Frauds, Collections Agent Matching/Channel Allocations across Retail and Commercial portfolios. Regulatory Capital and Economic Capital Models Liquidity Risk :Liquidity Models, Stress Testing Models, Basel Liquidity Reporting Standards Anti-Money Laundering (AML) :AML Scenarios/Alerts, Network Analysis Operational Risk :AMA Modeling, Operational Risk Reporting Modeling Techniques :Linear Regression, Logistic Regression, GLM, GBM, XGBoost, CatBoost, Neural Networks, Time Series (ARMA/ARIMA), ML Interpretability and Bias Algorithms Programming Languages & Tools :SAS, R, Python, Spark, Scala, Tableau, QlikView, PowerBI, SAS VA Strong understanding of Risk functions and their application in client discussions and project implementation. Additional Information: Masters Degree in a quantitative discipline (mathematics, statistics, economics, financial engineering, operations research) or MBA from top-tier universities Industry Certifications :FRM, PRM, CFA preferred Excellent Communication and Interpersonal Skills About Our Company | Accenture Qualification Experience :Minimum 7-12 years of relevant Risk Analytics experience, Exposure to Financial Services firms or Professional Services/Risk Advisory Educational Qualification :Masters degree in a quantitative discipline (mathematics, statistics, economics, financial engineering, operations research) or MBA from top-tier universities, Industry certifications such as FRM, PRM, CFA preferred

Python RWe are seeking a skilled Data Scientist proficient in Python and R to join our team The ideal candidate will have extensive experience developing machine learning and statistical models for regression, classification, and time series problems Additionally, they will have a strong understanding of software engineering principles and the ability to write clear, well structured, and testable code Key Responsibilities: Develop machine learning and statistical models for various business needs, including regression, classification, and time series analysis Implement models using Python and relevant libraries such as scikit learn, pandas, and numpy Apply machine learning techniques such as Linear Regression, Random Forest, Classification, and Ensemble methods Convert R code to Python and ensure seamless integration between the two languages Utilize R for data manipulation and analysis using tidyverse, dplyr, and data table Optimize and enhance existing R code for performance and scalability Collaborate with cross functional teams to understand business requirements and deliver data driven solutions Follow best practices in software engineering to produce clean, manageable, and testable code Stay updated with the latest industry trends and advancements in data science and machine learning Required Skills and Qualifications: Bachelor s or Master s degree in Computer Science, Statistics, Data Science, or a related field 6+ years of IT experience with a min of 3+ years in Data Science (AI/ML) Proven experience as a Data Scientist or similar role with hands on experience in Python and R Strong knowledge of machine learning algorithms and statistical modeling techniques Proficiency in Python libraries such as scikit learn, pandas, numpy, and matplotlib Expertise in R programming, particularly with tidyverse, dplyr, tidymodels, and data table Experience with relational databases and SQL Ability to convert R code to Python efficiently Familiarity with software engineering principles and best practices Strong problem solving skills and attention to detail Excellent communication and collaboration skills Ability to manage multiple projects and meet deadlines

Salary : 30 to 45 LPA Exp: 6 to 10 years Location :Hyderabad (Hybrid) Notice: Immediate to 30 days..!! Roles & responsibilities: 5+ years exp on Python , ML and Banking model development Interact with the client to understand their requirements and communicate / brainstorm solutions, model Development: Design, build, and implement credit risk model. Contribute to how analytical approach is structured for specification of analysis Contribute insights from conclusions of analysis that integrate with initial hypothesis and business objective. Independently address complex problems 5+ years exp on ML/Python (predictive modelling) . Design, implement, test, deploy and maintain innovative data and machine learning solutions to accelerate our business. Create experiments and prototype implementations of new learning algorithms and prediction techniques Collaborate with product managers, and stockholders to design and implement software solutions for science problems Use machine learning best practices to ensure a high standard of quality for all of the team deliverables Has experience working on unstructured data ( text ): Text cleaning, TFIDF, text vectorization Hands-on experience with IFRS 9 models and regulations. Data Analysis: Analyze large datasets to identify trends and risk factors, ensuring data quality and integrity. Statistical Analysis: Utilize advanced statistical methods to build robust models, leveraging expertise in R programming. Collaboration: Work closely with data scientists, business analysts, and other stakeholders to align models with business needs. Continuous Improvement: Stay updated with the latest methodologies and tools in credit risk modeling and R programming.

Salary : 20 to 35 LPA Exp: 3 to 8 years Location :/Gurugram/Bangalore/Hyderabad Notice: Immediate to 30 days..!! Roles & responsibilities: 3+ years exp on Python , ML and Banking model development Interact with the client to understand their requirements and communicate / brainstorm solutions, model Development: Design, build, and implement credit risk model. Contribute to how analytical approach is structured for specification of analysis Contribute insights from conclusions of analysis that integrate with initial hypothesis and business objective. Independently address complex problems 3+ years exp on ML/Python (predictive modelling) . Design, implement, test, deploy and maintain innovative data and machine learning solutions to accelerate our business. Create experiments and prototype implementations of new learning algorithms and prediction techniques Collaborate with product managers, and stockholders to design and implement software solutions for science problems Use machine learning best practices to ensure a high standard of quality for all of the team deliverables Has experience working on unstructured data ( text ): Text cleaning, TFIDF, text vectorization Hands-on experience with IFRS 9 models and regulations. Data Analysis: Analyze large datasets to identify trends and risk factors, ensuring data quality and integrity. Statistical Analysis: Utilize advanced statistical methods to build robust models, leveraging expertise in R programming. Collaboration: Work closely with data scientists, business analysts, and other stakeholders to align models with business needs. Continuous Improvement: Stay updated with the latest methodologies and tools in credit risk modeling and R programming.

About the role: This is a unique opportunity to join our fast-growing Data Science team. In the role of Data Scientist, you will execute large scale, high impact data modeling projects with responsibility for designing, developing, validating, socializing, operationalizing, and maintaining data-driven analytics that provide business insights to increase operational efficiency and customer value. What you will do: Deliver modeling and analytical insights to inform strategic and operational initiatives Conduct all phases of the model development process. Including: Understanding business issues, proposing technical solutions, data wrangling, data cleaning, data analysis, feature engineering, model selection, model development, model validation, model operationalization, presentation of results and insights, model implementation, model documentation Convert top-down business initiative requirements into actionable data analytics projects as well as conceiving and proposing a bottom-up analytics innovations Communicate technical solutions and results to business stakeholders Partner with business stakeholders, IT and lead the design and delivery ML solutions Inject the most applicable technology, including Machine Learning, Artificial Intelligence, Natural Language Processing and Statistical Modeling Continuously innovate with state of art techniques to improve the model What you will need: For Data Scientist 3-6 years & for Associate Data Scientist 1-3 years of experience in solving real life business problems using ML & Data Science Bachelor's degree is required. Master's degree preferred. Technical degrees with a concentration in statistics, data science, computer science or related field preferred In-depth knowledge of statistical methods & principles and its usage in the model building & data analysis Experience in applying descriptive, predictive, prescriptive models & data visualization to solve real life business problems Understanding of NLP concepts and its application is preferred Expertise in Python, SQL, Spark Experience with multiple modeling techniques such as: Time Series, Random Forests, Clustering, Neural Networks, Generalized Linear Models, Optimization, DOE, Dimensionality Reduction MLOps experience is preferred (implementing models/algorithms into production systems) Ability to work in a fast-paced environment and deliver against milestones Excellent communication skills in technical and business domains Proven ability to influence key stakeholders and leaders What you will get: Competitive salary, generous paid time off policy, charity match program, Group Medical Insurance, Parental Leave, Employee Assistance Program (EAP) and more! Collaborative, team-oriented culture that embraces diversity Professional development and unlimited growth opportunities

Role & responsibilities As a Principal Data Scientist in our AdTech team, youll drive innovation in our advertising platform using advanced machine learning and statistical methods. Youll tackle complex problems in real-time bidding, ad ranking optimization, budget efficiency, and performance measurement that directly impact our businesss bottom line. This role requires technical excellence and business acumen and youll collaborate with cross-functional teams to transform data insights into actionable strategies that enhance our advertising ecosystem. Preferred candidate profile B.Tech in Computer Science, Machine Learning, or a related field with at least 6+ years of experience in AI/ML research. Experience in auction theory, predictive modelling, causal inference, and reinforcement learning. Expertise in PyTorch or TensorFlow, and proficiency in Python as well as big data technologies. History of mentoring junior data scientists, and comfortable in driving multiple problem statements. Excellent communication skills, able to explain complex concepts to both technical and non-technical audiences. Design and develop sophisticated bidding, budget pacing and other algorithms that optimize ad spend or ROI. Create frameworks and experimental design to measure ad effectiveness and ROI. Collaborate with product and engineering teams to translate business requirements into efficient AI/ML solutions. Communicate long-term roadmap, 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.. Adtech domain experience is mandatory.

3-5 years experience of industry experience in developing data science models and solutions. Able to quickly pick up new programming languages, technologies, and frameworks Strong understanding of data structures and algorithms Ability to work in a start-up environment with a do it yourself attitude. Skill and Expertise Expert level proficiency in programming language Python/SQL. Working knowledge of Relational SQL and NoSQL databases, including Postgres , Redshift Exposure to open source tools & working on cloud platforms like AWS and Azure and being able to use their tools like Athena, Sagemaker, machine learning libraries is an added advantage Exposure to big data processing technologies like Pyspark, SparkSQL added advantage Exposure to AI tools LLM models Llama (ChatGPT, Bard) and prompt engineering is added advantage Exposure to visualization tools like Tableau, PowerBI is an added advantage Primary Responsibility As a senior analyst the individual will be providing technical expertise to the team Should be expert in all phases of model development (EDA, Hypothesis, Feature creation, Dimension reduction, Data set clean-up, Training models, Model selection, Validation and Deployment) Is expected to participate and lead discussions during the solution design phase. Should have deep understanding of statistical & machine learning methods ((logistic regression, SVM, decision tree, random forest, neural network), Regression (linear regression, decision tree, random forest, neural network), Classical optimisation (gradient descent etc), Must have thorough mathematical knowledge of correlation/causation, classification, recommenders, probability, stochastic processes, NLP, and how to implement them to a business problem. Expected to gain business understanding in health care domain order to come up with relevant analytics use cases. (E.g. HEOR / RWE / Survival modelling) Familiarity with NLP, Sentiment analysis, text mining , data scraping solutions. Dont meet every job requirementThats okay! Our company is dedicated to building a diverse, inclusive, and authentic workplace. If youre excited about this role, but your experience doesnt perfectly fit every qualification, we encourage you to apply anyway. You may be just the right person for this role or others.

Salary : 45 to 60LPA Exp: 12 to 20 years Location : Remote Notice: Immediate to 30 days..!! Roles & responsibilities: 10+ years exp on Python , ML and Banking model development Interact with the client to understand their requirements and communicate / brainstorm solutions, model Development: Design, build, and implement credit risk model. Contribute to how analytical approach is structured for specification of analysis Contribute insights from conclusions of analysis that integrate with initial hypothesis and business objective. Independently address complex problems 5+ years exp on ML/Python (predictive modelling) . Design, implement, test, deploy and maintain innovative data and machine learning solutions to accelerate our business. Create experiments and prototype implementations of new learning algorithms and prediction techniques Collaborate with product managers, and stockholders to design and implement software solutions for science problems Use machine learning best practices to ensure a high standard of quality for all of the team deliverables Has experience working on unstructured data ( text ): Text cleaning, TFIDF, text vectorization Hands-on experience with IFRS 9 models and regulations. Data Analysis: Analyze large datasets to identify trends and risk factors, ensuring data quality and integrity. Statistical Analysis: Utilize advanced statistical methods to build robust models, leveraging expertise in R programming. Collaboration: Work closely with data scientists, business analysts, and other stakeholders to align models with business needs. Continuous Improvement: Stay updated with the latest methodologies and tools in credit risk modeling and R programming.

Job Summary: The Senior Manager, Data Science will lead a team of data scientists to develop advanced analytical models and drive data-driven decision-making across the organization. This role requires a strong blend of technical expertise, strategic thinking, and leadership skills. The Senior Manager will collaborate with cross-functional teams to identify business opportunities, design and implement innovative data solutions, and contribute to the companys overall strategic goals. Key Responsibilities: 1. Leadership and Team Management: Lead, mentor, and develop a team of data scientists. Foster a culture of innovation, collaboration, and continuous learning. Set clear goals and performance expectations for the team. 2. Strategy and Vision: Define and implement the data science strategy aligned with the companys objectives. Identify and prioritize data science projects that drive business value. Stay abreast of industry trends and emerging technologies to keep the organization at the forefront of data science. 3. Technical Expertise: Oversee the development and deployment of machine learning models and algorithms. Ensure best practices in data modeling, coding, and experimental design. Provide technical guidance on complex data science projects. 4. Collaboration and Communication: Work closely with business leaders to understand their needs and translate them into data science initiatives. Communicate findings and recommendations to both technical and non-technical stakeholders. Collaborate with data engineering, IT, and other departments to ensure data availability and integrity. 5. Project Management: Manage multiple data science projects, ensuring timely and successful delivery. Allocate resources effectively and balance team workloads. Monitor project progress and make adjustments as needed. 6. Performance Measurement: Develop metrics to measure the impact and effectiveness of data science initiatives. Continuously evaluate and refine models and strategies based on performance data. Report on key performance indicators to senior management. Qualifications: Education: Bachelors degree in Data Science, Computer Science, Statistics, Mathematics, or a related field. Masters or Ph.D. preferred. Experience: 7+ years of experience in data science or a related field. 3+ years in a leadership or managerial role within a data science team. Proven track record of delivering impactful data science solutions in a business context. Technical Skills: Expertise in statistical analysis, machine learning, and predictive modeling. Proficiency in programming languages such as Python, R, or SQL. Experience with data visualization tools like Tableau, Power BI, or similar. Familiarity with big data technologies (e.g., Hadoop, Spark) and cloud platforms (e.g., AWS, Azure). Soft Skills: Strong analytical and problem-solving abilities. Excellent communication and presentation skills. Ability to translate complex technical concepts into actionable business insights. Strong organizational and project management skills. Preferred Qualifications: Experience in [specific industry or domain relevant to the company]. Knowledge of deep learning, NLP, or other advanced AI techniques. Experience with Agile methodologies and project management tools.

In this role, you will be required to build and develop advanced analytics capabilities and assets/accelerators. You will be responsible for all aspects of end-to-end Workforce Management capability creation, including Operations (forecasting, capacity planning, staffing, scheduling, real-time monitoring, and operations management reporting and analysis), Software Configuration, as well as Insight generation. It will be your responsibility to build and update Standard Operating Procedures (SOPs) for Workforce Management with appropriate participation from multiple Operations and Analytics teams. You will need to develop a forecasting, capacity planning, and scheduling strategy and framework that will enable the company to meet service levels, revenue goals, and operating parameters. You will own the workforce management team as they balance schedule adjustments, exceptions, adherence, mentorship, feedback, and training schedules. Additionally, you will evaluate the accuracy of forecasts and schedules prepared by the WFM team and act as the primary point of contact for data engineers to manage data effectively. You are required to have a Bachelors or Masters degree in a quantitative discipline such as Commerce, Statistics, Actuarial Sciences, Mathematics, Quantitative Finance, or Economics. Strong analytical skills with a solid understanding of statistics and predictive modeling are essential. Excellent knowledge of Contact center Operations is a must, and proficiency in the use of Dialer, workforce management software, CMS reporting, call recording, and monitoring systems is required. Demonstrating knowledge of call center metrics and WFM policies and procedures is essential. Experience in predictive modeling techniques such as GLM, Linear Regression, Time Series, Segmentation/Cluster Analysis, Decision Trees, and Random Forests is a must. Advanced proficiency with Microsoft Excel, including VBA, is required, along with basic database skills including SQL and the ability to pull together disparate data sources. Knowledge of statistical tools like R, SAS, SPSS, etc., is preferred. Analytical skills to provide insights on data trends and patterns critical to the business are necessary. Project/Program Management knowledge, including working on Architecture/Design of BI/Analytics solutions, is beneficial. You should have the ability to establish priorities, handle multiple assignments concurrently with minimal direction in a fast-paced work environment, and work both independently and as part of a team. Being self-disciplined and results-oriented are key qualities for this role. Preferred qualifications/skills include working knowledge of data entry and extraction through Verint/Genesis/NICE, understanding of scheduling functionality and forecasting through Verint/Genesis/NICE, and knowledge of real-time analysis using Verint/Genesis/NICE.,

The Manager - Data Science Product plays a crucial role in developing and delivering the product vision and roadmap in collaboration with product developers, data engineers, and data analysts at Majid Al Futtaim Retail. The focus is on spearheading the Advanced Analytics transformation within the organization. As part of the Retail Analytics Unit, the Manager will contribute to building and developing the analytics talent necessary to support the advanced analytics agenda. Team members are encouraged to shape the unit's trajectory and bring their ideas to life. The Manager will be instrumental in enhancing the Advanced Analytics value proposition in alignment with Majid Al Futtaim's digital and non-digital objectives. Responsibilities include designing, testing, and implementing data models, developing methodologies to estimate business value and track solution adoption, leveraging quantitative analysis expertise to build high-quality statistical models, and enhancing algorithms for structured/unstructured Retail Analytics problems. The Manager will lead the development of scalable models, validate and optimize model performance, run experiments to assess results, and develop impact measurement frameworks. Additionally, they will ideate and develop proof of concepts for new analytics initiatives, focusing on customer-centric approaches and optimizing user experience and business operations. Coordination and communication are essential aspects of the role, involving acting as a thought partner to the analytics team and key stakeholders, liaising with the product team, ensuring regular information exchange with stakeholders, and contributing to presentations on advanced analytics and performance. The Manager will also build relationships with key personnel, collaborate with stakeholders to ensure clarity on specifications, and support the development of policies and procedures for the Retail Analytics Unit. Furthermore, the Manager will be responsible for preparing business presentations and reports, conducting audits of processes and databases, and supporting the development and implementation of relevant policies and procedures. Minimum qualifications include a Bachelor's Degree in an IT-related field or Computer Engineering, with a preference for a Master's Degree in a similar field. The ideal candidate should have 5-8 years of experience in a senior Data Scientist role, preferably within the Retail/FMCG sector, along with expertise in visualization tools, programming languages, algorithm/modeling techniques, machine learning model deployment, and data visualization software. In summary, the Manager - Data Science Product at Majid Al Futtaim Retail will lead the development and delivery of the product vision and roadmap, contribute to the organization's Advanced Analytics transformation, and play a key role in enhancing the Advanced Analytics value proposition in alignment with long-term objectives. The role involves a diverse set of responsibilities, including designing data models, developing methodologies, leading solution development processes, and collaborating with stakeholders to drive business objectives and maintain strong partnerships.,

The opportunity: Support decision-making based on market data, collaborating on nurturing a data-driven culture. Gather, interpret data and analyze results using analytics, research methodologies and statistical techniques, assessing BU and GPGs needs, playing a key role during the M&S yearly cycle (mainly Market Input Market Outlook -MIMO, Strategic Planning, Global Target Setting -GTS). How you'll make an impact: Being the person of reference in the GPG, together with the GPMM, on the market intelligence and analytical tools, dashboards, excel-based files, SalesBI/ PowerBI /STRATOS/Anaplan/MIS. GPG Mekko/STRATOS preparation, production and alignment for the main Hitachi Energy Global processes: Global Target Setting (GTS) and Marketing Input Market Outputs -historical product and market review- (MIMO). Order Estimates, BU forecast models, Market sizes/shares, PIE by country/product/segment and Market/segment validation. Collect data and provide sound business and competitor intelligence analyses related to market and trends. Participate with Management to contribute to the definition of strategic plans and support relevant implementation. Support the key strategic initiatives of the GPG, collecting feedback and providing insights to improve hit-rate. Assist in the development of business analysis tools to support global, regional, and local marketing & sales teams (e.g. STRATOS/Anaplan). Support on the Demand vs supply Orders Received budget mapping (yearly, after GTS). Market Intelligence System (MIS) updates for the GPG. Master Data checks and validation for the related GPG. GPG Product portfolio analysis and support. Develop and implement data analyses, leverage data collection systems and other strategies that optimize statistical efficiency and quality in their GPG. Act as a liaison between HUBs, GPGs, and BU, analyzing and interpreting data involving company procedures, policies, and workflows. Evaluate key performance indicators (KPIs), provide ongoing reports, and recommend business plan updates. Proactively monitor and strive to maintain high levels of data quality and completeness. Extracting and analyzing data from sales/financial tools and other relevant sources to measure progress of specific activities or milestones for the defined processes and initiatives. Providing ad-hoc analysis based on business needs (channels, segments, geographic areas, top accounts). Developing and maintaining reports and dashboards (including but not limited to Salesforce.com). Responsible to ensure compliance with applicable external and internal regulations, procedures, and guidelines. Living Hitachi Energy's core values of safety and integrity, which means taking responsibility for your actions while caring for your colleagues and the business. Your Background: Bachelor's degree in engineering, mathematics, economics, or equivalent qualification. Experience collecting, organizing, analyzing, and disseminating abundant information with accuracy. Ability to write reports and present findings in a professional way (MS PowerPoint, Excel). Experience in SFDC and PowerBI for developing reports and dashboards. Basic Intermediate statistical knowledge: Linear Regression, Correlation, cross tabs, elementary probability, and intermediate logic would be beneficial. Intermediate change management skills: analysis, conclusion, recommend, present. Good marketing and sales experience (product knowledge and market drivers may help a lot while working on market estimation models). Strong attention to detail and ability to work under tight deadlines. Proactive and self-motivated. Passion, Integrity, and Energy. Excellent MS Excel/PowerPoint/SharePoint skills Proficiency in both spoken & written English language is required,

You should have 5 to 7 years of experience in Data Science or Machine Learning roles. Your proven ability should cover working on end-to-end ML projects, from research to production. It is essential to conduct in-depth machine learning research and stay updated with state-of-the-art advancements, including reading, interpreting, and implementing research papers, especially in the Generative AI domain. Your responsibilities will also include mentoring and guiding junior data scientists and interns in executing real-world projects. You should be able to design and build machine learning and deep learning models to solve complex business challenges. Working collaboratively across teams to turn data into decisions and models into products is a crucial aspect of the role. Having a strong foundation in Statistics and Probability is essential. You should also possess advanced proficiency in Python for data science and ML workflows. Hands-on experience with key libraries such as Scikit-learn, Keras, TensorFlow, and PyTorch is required. Expertise in core ML algorithms like Linear/Logistic Regression, Decision Trees, Gradient Descent, and SVMs is expected. Deep familiarity with Transformer architectures and working with Large Language Models (LLMs) is a plus. Experience with frameworks like Langchain or LlamaIndex for building LLM-based applications will be beneficial. Your ability to turn theoretical models into production-ready code with clarity and precision is highly valued in this role.,

The Manager - Data Science Product at Majid Al Futtaim Retail in India plays a crucial role in developing and delivering the product vision and roadmap in collaboration with product developers, data engineers, and data analysts. This position involves spearheading the Advanced Analytics transformation within the organization. The Manager will contribute to building analytics talent to support the advanced analytics agenda and shape the trajectory of the Retail Analytics Unit. By leveraging quantitative analysis, data mining, and data manipulation, the Manager will design and implement data models, develop advanced statistical models, and enhance algorithms to address Retail Analytics problems. Responsibilities also include leading the solution development process, running experiments to assess model results, and developing impact measurement frameworks. The Manager will ideate and develop proof of concepts for new analytics initiatives, aiming to optimize user experience and business operations. Additionally, the role involves coordinating with various stakeholders, liaising with the product team, and ensuring regular information exchange on project progress. Building relationships and maintaining partnerships with key personnel are essential to achieve organizational goals. Furthermore, the Manager will be responsible for preparing business presentations and reports related to Retail Analytics, performing regular audits of processes and databases, and contributing to the development and implementation of relevant policies and procedures. The ideal candidate should possess a Bachelor's Degree in an IT-related field or Computer Engineering, with a preference for a Master's Degree. A minimum of 5-8 years of experience in a senior Data Scientist role in an international environment, along with expertise in Retail/FMCG business, is required. Proficiency in programming languages like Python/SQL/PySpark, knowledge of algorithm/modeling techniques, and experience in deploying machine learning models on cloud services are essential skills for this role. The Manager - Data Science Product at Majid Al Futtaim Retail must have experience in visualization tools such as PowerBI, Qlik, and BO, as well as familiarity with various programming languages and modeling techniques. The candidate should also possess experience in deploying machine learning models on cloud services, time series forecasting, boosting algorithms, optimization techniques, NLP, recommendation systems, and data visualization software. Advanced experience in Azure, Spark, and git, along with a basic understanding of web application frameworks, is beneficial. Strong problem-solving skills, a collaborative mindset, and proactive attitude are essential attributes for this role.,

The TradeFinder Quant Analyst position based in Mumbai, India, falls under the Group Strategic Analytics (GSA) team at Deutsche Bank. The GSA team plays a crucial role in integrating analytics and technology across various units of the bank, including Investment Bank, Corporate Bank, and Risk and Control functions. The team focuses on developing a scalable and flexible Front Office pricing and risk management system that ensures consistency in analytics and technology platform to prevent arbitrage within the bank. As a TradeFinder Quant Analyst, your key responsibilities will include collaborating with global teams on quantitative and regulatory projects, understanding business problems, providing optimized solutions on a scalable platform, and implementing projects using Python and C++ programming languages. Effective communication with stakeholders worldwide is essential for the successful execution of projects. The ideal candidate will have a strong educational background in Engineering/Science, Economics, Statistics, or a related numerate discipline from reputable institutions like IIT or NIT. Proficiency in financial instruments, pricing models, and risk models is required, along with experience in applied econometrics. Certification courses such as CFA, FRM, or CQF will be advantageous. Candidates should have at least 3 years of programming experience in Python/C++ with a good understanding of Object-Oriented Programming concepts. Strong analytical skills, problem-solving instincts, and excellent communication abilities are essential for this role. The ability to work independently or collaboratively within multidisciplinary teams is crucial, along with a proactive approach to continuous learning and skill development. Deutsche Bank offers a supportive work environment with training, coaching, and flexible benefits to help employees excel in their careers. The company promotes a culture of empowerment, responsibility, commercial thinking, and collaboration to drive success. Diversity and inclusivity are valued, creating a positive and fair work environment for all employees. For more information about Deutsche Bank and its values, please visit the company website at https://www.db.com/company/company.htm. Join Deutsche Bank Group to be part of a team that strives for excellence and celebrates the successes of its people.,

Genpact (NYSE: G) is a global professional services and solutions firm dedicated to shaping the future through the delivery of impactful outcomes. With a workforce of over 125,000 individuals spanning across 30+ countries, we are inspired by our innate curiosity, entrepreneurial agility, and commitment to creating enduring value for our clients. Our purpose, driven by the relentless pursuit of a world that works better for people, empowers us to serve and transform major enterprises, including the Fortune Global 500, leveraging our deep business and industry expertise, digital operations services, and proficiency in data, technology, and AI. We are currently seeking applications for the position of Business Analyst - Data Scientist. As a part of this role, you will be tasked with the development and implementation of NLP models and algorithms, extracting insights from textual data, and collaborating with cross-functional teams to deliver AI solutions. Responsibilities: Model Development: - Proficiency in various statistical, ML, and ensemble algorithms. - Demonstrated expertise in Time series algorithms and forecasting use cases. - Ability to discern model-specific strengths and weaknesses and identify suitable models for different problem types. - Understanding of evaluation metrics and the ability to recommend the correct evaluation metric for a given problem. Data Analysis: - Extraction of meaningful insights from structured data. - Data preprocessing for ML/AI applications. Collaboration: - Close collaboration with data scientists, engineers, and business stakeholders. - Providing technical guidance and mentorship to team members. Integration and Deployment: - Integration of ML models into production systems. - Implementation of CI/CD pipelines for continuous integration and deployment. Documentation and Training: - Documentation of processes, models, and results. - Provision of training and support to stakeholders on NLP techniques and tools. Qualifications we seek in you: Minimum Qualifications/Skills: - Bachelor's degree in computer science, Engineering, or a related field. - Strong programming skills in Python and R. - Experience with DS frameworks (SKLEARN, NUMPY). - Knowledge of machine learning concepts and frameworks (TensorFlow, PyTorch). - Strong problem-solving and analytical skills. - Excellent communication and collaboration abilities. Preferred Qualifications/Skills: - Experience in Predictive Analytics and Machine Learning techniques. - Proficiency in Python/R/Any other open-source programming language. - Experience with visualization tools such as Tableau, Power BI, Qlikview, etc. - Applied statistics skills including distributions, statistical testing, regression, etc. - Knowledge and experience with various tools and techniques in Forecasting, Linear Regression, Logistic Regression, Regularization, Segmentation, Cluster Analysis, Factor Analysis, Machine Learning (Random Forest, Gradient Boosting, SVM, XGBoost, Deep Learning), etc. - Familiarity with big data technologies (Hadoop, Spark) and cloud platforms (AWS, Azure, GCP). This is a full-time position located in India-Hyderabad. If you are a dynamic professional with a passion for driving innovation and creating impactful solutions, we invite you to apply for this exciting opportunity.,

You will be heading the Data Analytics and AI team within the Enterprise Technology Group with a primary purpose of leading and developing a robust team focused on driving the company towards a data-first and data-driven organization. Your role will involve delivering and maintaining smart data-driven solutions essential for growth and operational efficiency. Accelerating the adoption and implementation of AI solutions to enhance innovation and competitive advantage will be a key aspect. Managing all aspects of new data analytics and AI projects from inception to delivery, including day-to-day operations, will be crucial, with a strong emphasis on assessing business value, ROI, and cost reduction. The ideal candidate should hold a Bachelor's or Master's degree in Computer Science, Math, Quantitative Methods, or Information Systems, with over 10 years of overall technology experience, including substantial experience in data analytics and AI. Proficiency in programming languages such as Python, R, or similar, as well as a deep understanding of algorithms like linear regression, logistic regression, decision trees, random forest, boosting algorithms (e.g., XGBoost), k-means, hierarchical clustering, and principal component analysis is preferred. Familiarity with data science concepts, statistical and mathematical methods, and various Data & AI technologies/tools is essential. Located in Mumbai, this is a full-time office-based position within the Enterprise Technology Group, reporting to the Head of the same group. The key responsibilities will include leading and developing a strong data analytics and AI team, establishing best practices for data analytics and responsible AI initiatives, managing all stages of AI and LLM projects, collaborating with stakeholders to gather requirements, and implementing advanced models and algorithms to solve complex business problems. Staying updated with the latest advancements in AI and LLM technologies will also be a critical aspect of the role. Key behavioral strengths required for this position include excellent analytical, problem-solving, and decision-making skills, proven leadership abilities, effective communication and collaboration skills, and the capacity to work with diverse stakeholders. Joining CulverMax Entertainment Pvt Ltd will offer you the opportunity to work with some of India's leading entertainment channels and OTT platforms, alongside a progressive and inclusive work culture that celebrates diversity and innovation. As a part of the team, you will contribute to creating exceptional content and experiences while being recognized as an Employer of Choice in various prestigious awards and accolades.,

You should have expertise in Generative AI with a good understanding of various techniques such as GANs, VAEs, and other relevant architectures. Your experience should include applying these techniques to real-world problems like image and text generation. Familiarity with Gen AI development tools like Prompt engineering, Langchain, Semantic Kernels, and Function calling is required. Exposure to both API-based and open-source LLMs based solution design is preferred. In terms of technical proficiency, you should have knowledge in machine learning algorithms including linear regression, logistic regression, decision trees, random forests, support vector machines, and neural networks. Proficiency in data science tools like NumPy, SciPy, Pandas, Matplotlib, TensorFlow, and Keras is essential. Experience with cloud computing platforms such as AWS, Azure, and GCP is also necessary. Additionally, familiarity with natural language processing (NLP), Transformer models, attention mechanisms, word embeddings, computer vision, convolutional neural networks, recurrent neural networks, object detection, robotics, reinforcement learning, motion planning, and control systems is required. Understanding data ethics including bias in machine learning and fairness in algorithms is also expected. As an Infoscion, your responsibilities will include diagnosing customer issues, designing innovative solutions, facilitating deployment, and ensuring client satisfaction. You will be involved in developing proposals, solution design, product configuration, conducting pilots, resolving queries, demonstrating solutions, and preparing effort estimates. Leading small projects and contributing to organizational initiatives to provide high-quality solutions to customers is also part of the role. Your primary skills should encompass Artificial Intelligence, Computer Vision, Big Data, and Natural Language Processing (NLP). Proficiency in Machine Learning with Python is a must. Moreover, you should have the ability to develop value-creating strategies, knowledge of software configuration management systems, and awareness of the latest technologies and industry trends. If you possess the required skills and are keen on helping clients navigate their digital transformation journey, this opportunity at Infosys is ideal for you.,

You will be part of Maruti Suzuki's Analytics Centre of Excellence (ACE) CoE team as a Data Scientist. Your responsibilities will include designing and implementing workflows of Linear and Logistic Regression, Ensemble Models (Random Forest, Boosting) using R/Python. You should have demonstrable competency in Probability and Statistics, with the ability to use ideas of Data Distributions, Hypothesis Testing, and other Statistical Tests. Experience in handling outliers, denoising data, and managing the impact of pandemic-like situations will be crucial. Additionally, you will be expected to perform Exploratory Data Analysis (EDA) of raw data, conduct feature engineering where applicable, and showcase competency in Data Visualization using the Python/R Data Science Stack. Leveraging cloud platforms for training and deploying large-scale solutions, as well as training and evaluating ML models using various machine learning and deep learning algorithms, will be part of your role. You will also need to retrain and maintain model accuracy in deployment and package & deploy large-scale models on on-premise systems using multiple approaches including docker. Taking complete ownership of the assigned project, working in Agile environments, and being well-versed with project tracking tools like JIRA or equivalent will be expected. Your competencies should include knowledge of cloud platforms (AWS, Azure, and GCP), exposure to NoSQL databases (MongoDB, Cassandra, Cosmos DB, HBase), and forecasting experience in products like SAP, Oracle, Power BI, Qlik, etc. Proficiency in Excel (Power Pivot, Power Query, Macros, Charts), experience with large datasets and distributed computing (Hive/Hadoop/Spark), and transfer learning using state-of-the-art models in different spaces such as vision, NLP, and speech will be beneficial. Integration with external services and Cloud API, as well as working with data annotation approaches and tools for text, images, and videos, will also be part of your responsibilities. The ideal candidate should have a minimum of 2 years and a maximum of 8 years of work experience, along with a Bachelor of Technology (B.Tech) or equivalent educational qualification.,

As a Model Validation/Audit/Review Specialist at KGS, your primary responsibility will be to conduct validation, audit, and review of credit loss forecasting models within the retail or wholesale domain, specifically focusing on IFRS9/IRB models and their PD/EAD/LGD components. In this role, you will need to understand relevant regulatory requirements, review development documentation, perform testing and benchmarking, create challenger models using SAS, R, or Python, and prepare comprehensive reports. Your duties will also include providing support for other model validation activities related to Underwriting scorecards, Credit Scoring, behavioral models, economic scenario models, and validation-related automation tasks as required. You will be responsible for assessing the conceptual soundness of models, critically evaluating testing conducted by developers, ensuring model integrity and accuracy, evaluating predictive power and robustness, and ensuring compliance with regulatory standards. Collaboration with seniors, AMs, and Managers will be essential to meet key project deliverables. You will be expected to take ownership of key deliverables, engage with Partners/Directors to understand project scope and business requirements, and coordinate with onshore and offshore teams for successful project delivery. Additionally, you will provide advice to non-audit clients on the implications of evolving provision accounting standards (IFRS9) and help them validate or develop credit risk measurement models. Qualifications for this role at KGS include an advanced degree in Mathematics, Statistics, Economics, or other analytical disciplines. Alternatively, a graduate degree along with an MBA in Finance and relevant experience or exposure will be considered. Additional certifications such as FRM or CFA are preferred. Ideal candidates should have 2-12 years of experience in Risk Management/Analytics at major banks, top-tier consulting firms like Big 4, or captives of well-known banks. Proficiency in programming languages such as Python, SAS, and R is required. Advanced skills in statistical and quantitative modeling, including various techniques like linear regression, logistic regression, ARIMA, Markov Chain, Merton Model, CHAID, and other predictive modeling methods, are essential. In-depth knowledge of regulatory requirements related to model risk management, such as SR11-7, SR15-18, PRA, and EBA guidelines, is also expected.,

As a Deep Learning Engineer Intern, you will have the opportunity to work on our core ML stack, focusing on areas such as Computer Vision, Recommendation Systems, and LLM-based Features (optional). Working closely with our senior engineers, you will gain hands-on experience with real data, address edge-case challenges, and rapidly iterate on prototypes that drive our food-robotic machine. You will be an integral part of a focused 2-person full-time ML team, serving as our first intern and reporting directly to the Lead. This small team size ensures significant mentorship opportunities and allows you to make a direct impact on product development. Your responsibilities will include: - Working on tasks such as Ingredient Segmentation, Recipe Similarity, and Vision-Language Models - Packaging and deploying models for on-device inference and AWS services - Supporting data collection and annotation, refining datasets based on model performance - Iterating on experiments, tuning hyperparameters, testing augmentations, and documenting results We are looking for candidates with: - Strong fundamentals in Deep Learning (Transformers, CNNs) and classical ML (Logistic / Linear regression) - Hands-on experience with PyTorch in academic projects, internships, or personal work - Proficiency in Python and the broader ML ecosystem (NumPy, pandas) - Solid understanding of training pipelines, evaluation metrics, and experimental rigor - Eagerness to learn new domains such as NLP and recommendations Nice to have skills include prior exposure to LLMs or multimodal models, experience with computer vision in challenging real-world environments, and projects involving noisy, real-world datasets or edge-case-heavy scenarios. Working with us, you will enjoy: - Early ownership of ML features, contributing end-to-end to projects - Hands-on experience with real robotic systems in homes, witnessing your models in action - Direct access to senior ML engineers for mentorship in a small, focused team environment - Rapid feedback loops that allow you to prototype, deploy, and learn quickly - A clear growth path with strong potential for full-time conversion into our rapidly expanding ML team We are looking for candidates who are currently enrolled in a B.Tech or M.Tech program (3-4 years into their degree), possess strong math and ML fundamentals beyond using off-the-shelf libraries, thrive in an ambiguous, fast-paced startup environment, and are always curious, enjoying building, experimenting, and sharing insights. Location: Bangalore (4 days WFO & 1 day WFH) Duration: 3-6 month internship Compensation: 1,00,000/month To apply, ensure your resume includes a project portfolio with the following: - GitHub profile showcasing ML/deep learning projects - Public codebase from coursework, internships, or personal work - Kaggle notebooks or competition solutions with leaderboard standings,

Genpact (NYSE: G) is a global professional services and solutions firm dedicated to shaping the future by delivering impactful outcomes. With a team of over 125,000 professionals spread across more than 30 countries, we are characterized by our inherent curiosity, entrepreneurial spirit, and commitment to creating enduring value for our clients. Fueled by our overarching purpose of continually striving towards a world that functions better for individuals, we partner with and enhance leading enterprises, including members of the prestigious Fortune Global 500. Our core competencies revolve around in-depth business and industry expertise, digital operational services, and proficiency in data, technology, and AI. We are currently seeking applications for the position of Business Analyst - Data Scientist to join our dynamic team. As a Business Analyst - Data Scientist at Genpact, you will play a pivotal role in the development and implementation of NLP (Natural Language Processing) models and algorithms, extracting actionable insights from textual data, and collaborating with cross-functional teams to deliver innovative AI solutions. **Responsibilities:** **Model Development:** - Proficiency in various statistical, machine learning, and ensemble algorithms. - Strong understanding of time series algorithms and forecasting use cases. - Ability to discern the strengths and weaknesses of different models and select appropriate ones for specific problems. - Proficiency in evaluating metrics and recommending suitable evaluation metrics for different problem types. **Data Analysis:** - Extracting meaningful insights from structured data. - Preprocessing data for machine learning/artificial intelligence applications. **Collaboration:** - Close collaboration with data scientists, engineers, and business stakeholders. - Providing technical guidance and mentorship to team members. **Integration and Deployment:** - Integrating machine learning models into production systems. - Implementing CI/CD pipelines for continuous integration and deployment. **Documentation and Training:** - Documenting processes, models, and results. - Providing training and support to stakeholders on NLP techniques and tools. **Qualifications we seek in you:** **Minimum Qualifications / Skills:** - Bachelor's degree in computer science, engineering, or a related field. - Proficient programming skills in Python and R. - Experience with data science frameworks such as SKLEARN and NUMPY. - Knowledge of machine learning concepts and frameworks like TensorFlow and PyTorch. - Strong problem-solving and analytical capabilities. - Excellent communication and collaboration skills. **Preferred Qualifications/Skills:** - Experience in predictive analytics and machine learning techniques. - Proficiency in Python/R or any other open-source programming language. - Building and implementing models, using algorithms, and running simulations with various tools. - Familiarity with visualization tools such as Tableau, Power BI, Qlikview, etc. - Proficiency in applied statistics skills, including distributions, statistical testing, regression, etc. - Knowledge and experience in various tools and techniques like forecasting, linear regression, logistic regression, machine learning algorithms (e.g., Random Forest, Gradient Boosting, SVM, XGBoost, Deep Learning), etc. - Experience with big data technologies (Hadoop, Spark). - Familiarity with cloud platforms like AWS, Azure, GCP. **Job Details:** **Title:** Business Analyst - Data Scientist **Primary Location:** India-Hyderabad **Education Level:** Bachelor's / Graduation / Equivalent **Job Posting:** Apr 1, 2025, 2:47:23 AM **Unposting Date:** May 1, 2025, 1:29:00 PM **Master Skills List:** Digital **Job Category:** Full Time,

Become part of our team! Team introduction Department of Data and Analytics has its hub at DTICI Bengaluru India catering to data and analytics requirements for Daimler Truck. we are 150+ strong team comprising of Data engineers, Data scientists, AI engineers and Analysts What makes the team/department special Highly energetic and young team that solves business problems that have the potential to define we build our trucks Good Communication & presentation skills. Strong Knowledge of Azure Components Azure Data Lake, Azure Data Factory, Azure SQL, Azure Databricks Master in Statistics/Machine Learning/Economics/ Big Data analytics (Full -Time) Strong experience in object-oriented programming using Python & PySpark Experience developing, training, and evaluating (supervised/unsupervised) machine learning models such as linear regression, Logistic regression, k-means, time series forecasting, Hypothesis testing (ANOVA, t-test, etc.), random forest, SVMs, Naive Bayes, gradient boosting, kNN, Deep learning algorithms like CNN, ANN and Reinforcement learning, Anomaly detection Familiar with statistical distributions, correlation analysis, descriptive statistics, ROC, F1-Score, etc. Proficiency in Python, Scikit-learn and ML libraries. Strong understanding of statistical modeling and data preprocessing. Should have had at least 2 to 3 use cases where the candidate would have gained the experience of end to end development of Data science solution and deployment Problem definition - white boarding Hypothesis building and testing and Exploratory data analysis Data engineering to curate data for model Training, testing, deployment and MLops Job Title: Data Scientist (Iterative Model Development Traditional ML) Job Summary: We are seeking a Data Scientist with expertise in building and optimizing traditional ML models, specifically within the automobile domain. The ideal candidate will have strong experience in classical ML algorithms, survival models, time series, statistical modelling, and deployment of predictive models. Experience with streaming data and telematics data solutions is highly desirable. Key Responsibilities: Work with Daimler s Businesses and Enabling Areas to support key business functions Contribute to storyboarding our results, support recommendations for an executive-level audience and produce leadership-quality deliverables Develop and optimize traditional ML models (regression, decision trees, SVM, XGBoost, etc.) with strong knowledge on Hypothesis testing. Perform feature engineering and dataset preprocessing for model training. Build scalable machine learning pipelines for real-world applications. Work on time series forecasting, anomaly detection, recommendation systems, etc. Optimize model performance using hyperparameter tuning and cross-validation. Deploy ML models into production using cloud and on-premises solutions. Collaborate with cross-functional teams to integrate ML models into business processes. Analyze and interpret telematics data to derive actionable insights. Develop solutions for streaming data processing and real-time analytics.

You should have the ability to design and implement workflows of Linear and Logistic Regression, Ensemble Models (Random Forest, Boosting) using R/Python. Demonstrating competency in Probability and Statistics, you should be capable of utilizing ideas of Data Distributions, Hypothesis Testing, and other Statistical Tests. Your experience should include dealing with outliers, denoising data, and handling the impact of pandemic like situations. Performing Exploratory Data Analysis (EDA) of raw data and feature engineering wherever applicable is crucial. You should possess demonstrable competency in Data Visualization using the Python/R Data Science Stack. Leveraging cloud platforms for training and deploying large-scale solutions is essential. Being able to train and evaluate ML models using various machine learning and deep learning algorithms is a must. You should also be skilled in retraining and maintaining model accuracy in deployment. Knowledge of cloud platforms such as AWS, Azure, and GCP is required. Exposure to NoSQL databases (MongoDB, Cassandra, Cosmos DB, HBase) is preferred. An understanding of forecasting experience in products like SAP, Oracle, Power BI, and Qlik is beneficial. Proficiency in Excel (Power Pivot, Power Query, Macros, Charts) is expected. Having experience with large datasets and distributed computing (Hive/Hadoop/Spark) is advantageous. Knowledge of transfer learning using state-of-the-art models in different spaces like vision, NLP, and speech is a plus. Integration with external services and Cloud API is also a part of the role. Working with data annotation approaches and tools for text, images, and videos is desirable. You should be able to package and deploy large-scale models on on-premise systems using multiple approaches, including Docker. Taking complete ownership of the assigned project is necessary. Experience of working in Agile environments and being well-versed with JIRA or equivalent project tracking tools is expected.,