1143 Statistical Modeling Jobs - Page 15

As a Senior Specialist in Global Data Science at Colgate-Palmolive, you will play a crucial role in the GLOBAL DATA SCIENCE & ADVANCED ANALYTICS vertical. This department focuses on working on business cases with significant financial impacts for the company, providing solutions to business questions, recommended actions, and scalability options across markets. Your position as a Data Scientist will involve leading projects within the Analytics Continuum, where you will be responsible for conceptualizing and developing machine learning, predictive modeling, simulations, and optimization solutions aimed at achieving clear financial objectives for Colgate-Palmolive. Your responsibilities will include building predictive modeling solutions, applying ML and AI algorithms to analytics, developing end-to-end business solutions from data extraction to building business presentations, conducting model validations, and continuous improvement of algorithms. You will also deploy models using Airflow and Docker on Google Cloud Platforms, own Pricing and Promotion, Marketing Mix projects, and present insights to business teams in an easily interpretable manner. To qualify for this role, you should have a BE/BTECH in Computer Science or Information Technology, an MBA or PGDM in Business Analytics or Data Science, additional certifications in Data Science, or an MSC/MSTAT in Economics or Statistics. You should have at least 5 years of experience in building statistical models, hands-on experience with coding languages such as Python and SQL, and knowledge of visualization frameworks like PyDash, Flask, and PlotLy. Understanding of Cloud Frameworks like Google Cloud and Snowflake is essential. Preferred qualifications include experience in managing statistical models for Revenue Growth Management or Marketing Mix models, familiarity with third-party data sources, knowledge of machine learning techniques, and experience with Google Cloud products. At Colgate-Palmolive, we are committed to fostering an inclusive environment where individuals with diverse backgrounds and perspectives can thrive. Our goal is to develop talent that best serves our consumers globally and ensure that everyone feels a sense of belonging within our organization. We are an Equal Opportunity Employer dedicated to empowering all individuals to contribute meaningfully to our business.,

You will be joining our team as a Manager or Assistant Manager in Data Analytics. Your role will involve developing analytical frameworks, deriving business insights, and driving data-led decision-making. A strong analytical mindset, business acumen, and end-to-end data project management skills are crucial for this position. Your responsibilities will include analyzing complex datasets to identify trends, patterns, and actionable insights. You will create dashboards, reports, and visualizations using tools such as Power BI, Tableau, or similar software. Collaboration with cross-functional teams like Marketing, Sales, Finance, and Operations to understand data requirements and provide solutions will be a key aspect of your role. Furthermore, building predictive and prescriptive models to aid strategic decisions is essential. In terms of project management, you will be tasked with overseeing and prioritizing multiple analytics projects with tight deadlines. Translating business challenges into structured analytical use cases and working closely with data engineering and IT teams to ensure data accuracy and system integration are also part of your responsibilities. Engaging with senior stakeholders to gather requirements and present findings, mentoring junior analysts or interns (for Manager-level role), and promoting a data-driven culture within the organization will be important aspects of your role. You should be proficient in SQL and at least one programming language (Python, R, etc.). Expertise in data visualization tools like Power BI and Tableau, hands-on experience with statistical modeling and machine learning, strong problem-solving, communication, and storytelling skills are required. Additionally, the ability to work independently and manage ambiguity is crucial. A Bachelor's/Master's degree in Data Science, Statistics, Computer Science, Engineering, Economics, or a related field is necessary. For the Manager role, 6-10 years of relevant experience in data analytics or business intelligence is required, while for the Assistant Manager role, 3-6 years of experience is needed. Experience in leading analytics initiatives and delivering measurable impact is essential. Preferred qualifications include experience in specific domains like BFSI, Retail, E-commerce, or Telecom, as well as certifications in Data Analytics / BI tools. It is advantageous if you have worked with cloud platforms like AWS, Azure, or GCP for data storage and computation, and if you ensure adherence to data governance and security standards.,

The Demand Planning Center of Excellence (COE) Lead at Apollo Tyres Ltd plays a crucial role in enhancing demand planning practices across global operations. Your primary responsibility is to establish and maintain demand planning capabilities, ensuring the implementation of standardized processes and tools to achieve accurate demand forecasting and inventory optimization. Collaborating with regional demand planning teams, sales, marketing, finance, and supply chain functions is essential to drive efficiency and effectiveness in demand planning. Developing and executing a comprehensive Demand Planning COE strategy aligned with global supply chain objectives is a key initiative. Leading the design, deployment, and continuous improvement of demand planning processes, systems, and tools is vital for achieving best-in-class practices. Providing subject matter expertise and training to regional teams on demand planning methodologies and tools will be a core activity to ensure alignment and consistency. Navigating the complex cross-functional environment will require influencing stakeholders across regions, geographies, and channels. Collaboration with diverse partners in process, data, product, and IT domains is necessary to achieve common goals. Integration of IBP business requirements with technological solutions across global and regional operations is critical for seamless operations. Facilitating collaboration between sales, marketing, supply chain, and finance functions is essential to align demand forecasts with business objectives. Leading scenario planning, demand sensing, and predictive analytics initiatives will be instrumental in enhancing forecast accuracy. Acting as the custodian for advanced planning solutions and ensuring successful adoption of digital and AI-based demand planning tools is a core responsibility. Providing leadership and mentorship to demand planners across regions, fostering a culture of continuous learning and collaboration, is imperative. Managing cross-functional projects related to demand planning improvements, ensuring timely delivery and stakeholder alignment, is crucial for operational efficiency. Possessing knowledge of O9/Blue Yonder will be advantageous in executing duties effectively. Your internal relationships will involve collaboration with functional heads and managers, supply and demand planning teams, sales and marketing, finance, manufacturing IT teams, logistic teams, and cross-departmental project stakeholders. Externally, you will engage with project implementation vendors and OE Partners like O9 and S4 HANA. The ideal candidate will have at least 7 years of experience in demand planning, supply chain management, or related roles within a global manufacturing environment. Proficiency in demand planning processes, statistical modeling, and forecasting techniques is essential. Experience with demand planning tools and data visualization tools, along with strong leadership and project management skills, is required. Excellent communication, analytical, and problem-solving skills are critical for success in this role. Educational qualifications preferred include a Master's Degree/MBA from a reputed institute, with a Bachelor's degree in Business, Supply Chain, or Technology. Challenges in this role include stakeholder management, legacy process revamp, fostering an agile ecosystem, change management, and driving technological advancements in demand planning processes.,

As a Senior Analytics Consultant specializing in banking analytics, you will leverage your expertise in credit risk modeling, fraud detection, and marketing analytics to lead client-facing engagements. With over 5 years of experience in the banking sector, you will be responsible for designing and implementing advanced models, translating data insights into strategic recommendations, and ensuring compliance with regulatory standards. Your key responsibilities will include leading and managing analytics projects focused on credit risk, fraud analytics, or marketing analytics within the banking industry. You will collaborate with clients to define business problems, develop analytic frameworks, and deliver actionable solutions. Using your proficiency in analytical programming languages such as Python, R, or SAS, you will build and validate statistical and machine learning models to extract meaningful insights from large datasets. In addition to your technical skills, you will be expected to communicate complex analytical findings effectively through business-friendly presentations and reports. As a senior member of the team, you will also guide junior team members, contribute to knowledge sharing within the firm, and uphold a strong understanding of the banking regulatory environment, including standards like Basel II/III, CCAR, and AML. To qualify for this role, you should hold a Bachelors or Masters degree in Statistics, Economics, Mathematics, Computer Science, or a related quantitative discipline. You must have a minimum of 5 years of hands-on experience in banking analytics, strong proficiency in SQL, and a solid understanding of statistical modeling techniques and machine learning algorithms. Prior experience in a consulting or professional services environment, familiarity with cloud-based analytics platforms, and exposure to digital banking data sources are preferred qualifications. In return, you can expect high-impact projects with top banking institutions, a collaborative team culture that values intellectual curiosity, clear paths for career growth and leadership opportunities, and competitive compensation. Join us in shaping the future of banking analytics and making a significant impact in the industry.,

This exciting opportunity is responsible for providing Asset Predictive Analytics (APA) support for industrial clients. You will be utilizing data analysis and machine learning techniques to predict potential failures and optimize maintenance strategies for mechanical equipment. Your role will require a strong understanding of mechanical systems, data analysis, and predictive modeling to improve equipment reliability and reduce downtime. You will be responsible for implementing Asset Predictive Analytics (APA) for major rotating and static equipment such as compressors, pumps, gas turbines, steam turbines, motors, blowers, fans, fired heaters, distillation columns, transformers, and heat exchangers. This will involve conducting data collection and analysis, developing predictive models using machine learning algorithms, and optimizing maintenance schedules based on predicted failure risks. Additionally, you will collaborate with maintenance teams to implement optimized maintenance plans. To be successful in this role, you must hold a B.E/B.Tech degree in Mechanical or Chemical Engineering or equivalent from a recognized university. You should have a minimum of 5-7 plus years of experience in Asset Predictive Analytics in industrial sectors, preferably oil & gas. Knowledge of reliability principles, tools, methodologies, and experience with AVEVA Predictive Analytics or similar solutions are essential. You should possess a strong understanding of mechanical systems and equipment, proficiency in data analysis, statistical modeling, and programming languages such as Python, R, or others commonly used for data analysis and machine learning. Experience in developing and implementing predictive models using machine learning algorithms is required. Effective communication skills to convey technical information to both technical and non-technical audiences are crucial. Furthermore, you should have experience with CMMS, SCADA, and other relevant software and tools, as well as competency in fault analysis of rotating machinery and static equipment. Strong interpersonal skills, a collaborative approach, passion, commitment, self-awareness, and a systematic approach to work with high attention to detail are key competencies for this role. This position will involve engaging with client/team stakeholders at a senior level. As part of the role, you will be working with clients in Energy, Oil & Gas, Refining, Petrochemicals, Chemicals, Mining, Supply Chain, Utilities, Power, and Manufacturing industries. Travel may be required based on business needs. In summary, the role of Asset Predictive Analytics (APA) support for industrial clients involves utilizing data analysis, machine learning techniques, and predictive modeling to enhance equipment reliability and reduce downtime. This position requires a strong mechanical engineering background, expertise in data analysis and statistical modeling, and the ability to communicate technical information effectively.,

The Specialized Analytics Manager provides full leadership and supervisory responsibility, offering operational/service guidance to team(s) and applying deep disciplinary knowledge to provide value-added perspectives or advisory services. You may contribute to developing new techniques, models, and plans within your area of expertise. Excellent communication and diplomacy are essential skills for this role. You will be responsible for the volume, quality, and timeliness of end results, as well as shared accountability for planning and budgets. Your work will impact an entire area, influencing the overall performance and effectiveness of the sub-function/job family. As a manager, you will have full supervisory responsibility, ensuring team motivation and development through professional leadership, including performance evaluation, compensation, hiring, disciplinary actions, and task delegation. Responsibilities: - Drive multiple projects involving large and complex data sets for analysis/validation, utilizing programming tools such as SQL, SAS, and SAS Macro at a proficient level - Utilize your understanding of Credit card business financials to make financial estimates based on macro-economic and historical trends - Analyze Credit card portfolios, focusing on interest rates, fees, interchange, penalties, and other related aspects - Collaborate with internal and global stakeholders to achieve tangible outcomes - Lead and mentor a team of 10-20 members - Engage with business partners regularly to grasp their strategic priorities, provide context, and propose proactive solutions - Enhance processes and strategies by exploring new data sources, tools, and capabilities - Demonstrate strong storytelling and influencing skills - Work with large and complex data sets to evaluate, recommend, and support the implementation of business strategies - Identify and compile data sets using tools like SQL and Access to predict, improve, and measure the success of key business outcomes - Document data requirements, data collection/processing/cleaning, and exploratory data analysis, potentially employing statistical models/algorithms and data visualization techniques - Be referred to as a Data Scientist in this role - Specialize in marketing, risk, digital, and AML fields as needed - Assess risk appropriately in business decisions, considering the firm's reputation and compliance with laws and regulations while maintaining ethical standards and accountability Qualifications: - 8-12 years of experience - Experience in a People Manager role - Understanding of Adobe Analytics - Proficiency in SAS and Python - Strong communication skills for coordination with senior business leaders - Knowledge of financials and PNL metrics, particularly in the financial services sector and credit card business - Exposure to Digital Business and familiarity with Digital Performance KPIs Education: - Masters Preferred This job description offers a comprehensive overview of the role's responsibilities and qualifications. Additional job-related duties may be assigned as necessary.,

At PwC, the focus in data and analytics is on leveraging data to drive insights and make informed business decisions. Advanced analytics techniques are utilized to help clients optimize operations and achieve strategic goals. In the role of data analysis at PwC, you will concentrate on using advanced analytical techniques to extract insights from large datasets and enable data-driven decision-making. Your responsibilities will include leveraging skills in data manipulation, visualization, and statistical modeling to assist clients in solving complex business problems. A Fraud/AML Risk Analytics Professional at PwC will be responsible for developing, validating, auditing, and maintaining AI/ML/NLP models for Fraud/AML/Credit risk. Candidates are expected to support financial institutions in meeting jurisdictional regulatory requirements and broader risk management initiatives. Key responsibilities include: - Developing and validating AI/ML/NLP models for Fraud/AML/Credit risk - Supporting financial institutions in meeting regulatory requirements and risk management initiatives - Utilizing advanced analytics techniques to extract insights from large datasets - Leveraging skills in data manipulation, visualization, and statistical modeling - Building meaningful client connections and learning to manage and inspire others - Growing personal brand and deepening technical expertise - Delivering quality work while embracing ambiguity and seeking opportunities to grow Core Skill Requirements: - 3-7 years of experience in Machine Learning/Artificial Intelligence, Natural Language Programming, Statistical/Mathematical modeling, quantitative research, Fraud/AML risk management, or related Credit Risk field - Proficiency in Machine learning algorithms like Random Forest, SVM, Neural Network, etc. - Experience in AML Scenario development, enhancement, and initial threshold setting and tuning - Proficiency in analytical tools such as Python, PySpark, Data Science, and cloud-based analytics - Business knowledge in transaction monitoring system, sanction screening, trade surveillance - Strong knowledge of fraud data analysis, strategy design, and delivery deployment Non-functional Skill Requirements: - Understanding of market trends and demands in the financial services sector - Excellent oral and written communication skills - Solid analytical and problem-solving skills - Process orientation with attention to detail - Industry knowledge of financial products - Willingness to travel to meet client needs Educational Background: - Master's degree or higher in a quantitative discipline - Industry relevant certifications such as CQF, FRM, CFA, CPA are a plus Additional Requirements For Senior Positions: - Consulting skills to structure and conceptualize solutions for complex problems - Experience in leading large risk analytics engagements independently - Ability to support sales pursuits for risk analytics offerings - Strong conceptual understanding of various functional/technical skills - Ability to drive innovation and thought leadership in risk management This role at PwC offers the opportunity to work with cutting-edge technologies and make a significant impact in the field of data analytics and risk management.,

You are an experienced Senior Quantitative Analyst specializing in credit risk modeling, especially focused on Internal Credit Risk Rating modeling. Your role involves leading the end-to-end development and validation of advanced credit risk models, with an emphasis on Expert judgement-based PD models for various sectors. You will work on data preparation and preprocessing using tools like SAS, Python, R, and SQL. Collaboration with cross-functional stakeholders is key to analyze and interpret complex model results and insights. Your responsibilities also include developing technical documentation for regulatory compliance, test plans, validation reports, and business requirements documents. Continuous model improvement is expected through optimization, implementing advanced modeling techniques, and enhancing predictive accuracy. Mentorship and technical guidance to junior team members are essential to foster knowledge sharing and professional development. Required qualifications include 5-10 years of hands-on experience in credit risk model development, expertise in modeling across retail and wholesale credit portfolios, proficiency in SAS, Python, R, SQL, deep understanding of IFRS9 and CECL regulatory frameworks, analytical skills, and excellent communication abilities. Preferred qualifications include an advanced degree in Statistics, Mathematics, Economics, or related field, professional certifications in risk management or financial modeling, experience with IRB modeling, machine learning techniques, and knowledge of Basel regulatory guidance. Technical skills required for the role encompass Model Development (PD, LGD, EAD, Qualitative PD Models), Programming (SAS, Python, R, SQL), Regulatory Knowledge (IRB, IFRS9, CECL), Statistical Modeling, Data Preprocessing, and Machine Learning Techniques.,

Urgent Hiring for MNC for Model Validation role, which includes- Wholesale Fraud analytics model, Machine learning, model validation Experience in Wholesale IRB model development/validation Kindly send your updated CV at jatin@smrd.in

At American Express, our culture is built on a 175-year history of innovation, shared values and Leadership Behaviors, and an unwavering commitment to back our customers, communities, and colleagues. As part of Team Amex, youll experience this powerful backing with comprehensive support for your holistic well-being and many opportunities to learn new skills, develop as a leader, and grow your career. Here, your voice and ideas matter, your work makes an impact, and together, you will help us define the future of American Express. How will you make an impact in this role? Model Risk Management Group (MRMG) is responsible for the model risk management of all American Express models. The role will report to Head of MRMG and lead some of India teams to manage enterprise-wide model risk. The successful candidate will be responsible to manage and control model risk in order to elevate model excellence, strengthen long term shareholder value, and adapt to the changing landscape of both model development innovation, external environment and heightened regulatory expectations. Responsibilities include: Oversee and own independent validation of enterprise-wide models including marketing models Lead visionary research to explore opportunities to elevate model excellence and drive business impact Oversee and support regulatory and audit examinations Effectively communicate key outcomes of model risk management activities to senior management, business partners and regulators Take timely actions to ensure a consistent high-level performance in line with the company s winning framework and priorities Motivate staff and leaders across teams to deliver at optimal levels. Qualifications: Core competencies at leading roles related to model risk management or statistical modeling to deal with complex business problems Proven people leadership experience with the ability to lead, motivate and mentor highly competent and multi-layered teams, dispersed geographically Demonstrated ability and project leadership to lead large scale MRM initiatives Exceptional ability to build, leverage, and maintain relationships with senior leaders, business partners, and regulators Proven record of designing strategies and communicating effectively to bring senior management and diverse stakeholders on board. Experience with managing regulators, working with external/ internal auditors preferred. Understand the evolving compliance and regulatory requirements with key focus on gaps to stabilize and eliminate vulnerabilities in MRM Deep understanding in Machine Learning models (e.g., Gradient Boosting Machine, XGBoost, and Neural Network) as well as classic statistical modeling techniques and assumptions Degree with quantitative background or equivalent experience Must Have: 10+ years of work experience Must have worked in a GSIB in the field of model risk Good in-depth understanding of machine learning techniques like GBM, Random Forest etc. Should have modeling experience on marketing models. Need to have the aptitude to read research papers and turn them into actionable items for MRM (bring external perspective) Aptitude to think independently to come up with innovative solutions

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 : Data Science Good to have skills : NAMinimum 3 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 cross-functional teams to understand business needs, analyzing data to derive insights, and presenting your findings to stakeholders to support strategic decisions. You will also measure and justify the value of AI and machine learning solutions, ensuring they align with organizational goals and deliver tangible results. Roles & Responsibilities:- Expected to perform independently and become an SME.- Required active participation/contribution in team discussions.- Contribute in providing solutions to work related problems.- Analyze complex datasets to extract actionable insights that inform business strategies.- Collaborate with stakeholders to define project requirements and deliverables. Professional & Technical Skills: - Must To Have Skills: Proficiency in Data Science.- Strong understanding of machine learning algorithms and their applications.- Experience with data manipulation and analysis using programming languages such as Python or R.- Familiarity with data visualization tools to effectively communicate findings.- Ability to work with large datasets and perform statistical analysis. Additional Information:- The candidate should have minimum 3 years of experience in Data Science.- This position is based at our Bengaluru office.- A 15 years full time education is required. Qualification 15 years full time education

The group you ll be a part of The Global Information Systems Group is dedicated to the success of Lam through providing best-in-class and innovative information system solutions and services. Together, we support users globally with data, information, and systems to achieve their business objectives. The impact you ll make Performs statistical modeling and analysis of structured and unstructured datasets to develop metrics, reports and visualizations of trends and patterns. Works with technology organization and business end-users to understand data and analysis needs to develop technical requirements. Partners with development and data management roles to identify and capture data required from internal and external sources. Creates and maintains statistical models for ongoing and ad hoc review and analysis of data. Uses data visualization programs, tools and techniques to generate dashboards, reports and presentations that aid in data storytelling, understanding and interpretation of trends and patterns of business importance. May be internal or external, client-focused, working in conjunction with Professional Services and outsourcing functions. May include company-wide, web-enabled solutions. What you ll do Who we re looking for Typically requires a minimum of 8 years of related experience with a Bachelor s degree; or 6 years and a Master s degree; or a PhD with 3 years experience; or equivalent experience. Preferred qualifications Our commitment We believe it is important for every person to feel valued, included, and empowered to achieve their full potential. By bringing unique individuals and viewpoints together, we achieve extraordinary results. Lam Research ("Lam" or the "Company") is an equal opportunity employer. Lam is committed to and reaffirms support of equal opportunity in employment and non-discrimination in employment policies, practices and procedures on the basis of race, religious creed, color, national origin, ancestry, physical disability, mental disability, medical condition, genetic information, marital status, sex (including pregnancy, childbirth and related medical conditions), gender, gender identity, gender expression, age, sexual orientation, or military and veteran status or any other category protected by applicable federal, state, or local laws. It is the Companys intention to comply with all applicable laws and regulations. Company policy prohibits unlawful discrimination against applicants or employees. Lam offers a variety of work location models based on the needs of each role. Our hybrid roles combine the benefits of on-site collaboration with colleagues and the flexibility to work remotely and fall into two categories - On-site Flex and Virtual Flex. On-site Flex you ll work 3+ days per week on-site at a Lam or customer/supplier location, with the opportunity to work remotely for the balance of the week. Virtual Flex you ll work 1-2 days per week on-site at a Lam or customer/supplier location, and remotely the rest of the time.

Why would you like to join us? TransOrg Analytics specializes in Data Science, Data Engineering and Generative AI, providing advanced analytics solutions to industry leaders and Fortune 500 companies across India, US, APAC and the Middle East. We leverage data science to streamline, optimize, and accelerate our clients' businesses. Visit at www.transorg.com to know more about us. Job Location Gurgaon /Mumbai What do we expect from you? Analyze & interpret data and communicate results to clients, often with the aid of Mathematical/statistical techniques and software. This role requires: Data exploration, statistical/ predictive modelling, data analysis and hypothesis testing. Design, development and deployment of Predictive models and frameworks. Complex statistical concepts are explained in a way that clients can understand and advice on strategy. What do you need to excel at? Well-versed in quantitative analysis, data mining, trend analysis, customer profiling, clustering and predictive modelling. Executing the data-driven planning process by building models and frameworks that connect business unit drivers to company financials and forecast to take the correct decision as per the business need. Should be able to handle assigned tasks in the capacity of individual contributor. Demonstrate excellent teamwork. Collaborate with other data analysts to provide development coverage, support, and Knowledge sharing and mentoring of junior team members. What are we looking for? Bachelor's in Computer Science, Engineering, Statistics, Maths or related quantitative degree. 3-5 years of relevant experience in a data analysis or related role. Experience in BFSI and CPG Domain is Preferred. Experience of data pre-processing and data manipulation using Python or SQL Should have some experience of statistical analysis and modeling techniques (e.g., regression, classification, clustering). Experience with machine learning, deep learning frameworks and libraries ( good to have) Familiarity with data processing tools and frameworks Experience with data visualization tools like Tableau or Power BI. Track record of managing data project delivery including ability to meet deadlines, overcome challenges, manage stakeholder expectations, and produce clear deliverables Strong problem-solving skills with a keen attention to detail. Ability to think critically and provide data-backed insights. Excellent communication skills, both verbal and written. Understanding of Cloud Platforms (e.g. Azure / AWS/GCP) and ability to use them for developing, training and testing deep learning models ( good to have) Familiarity with cloud-based data warehousing platforms (snowflake) ( good to have)

Job Title:Senior Data AnalystExperience5-10 YearsLocation:Remote : As a Senior Data Analyst, you will provide invaluable insights to our product and Business teams, working closely with our product and engineering leaders. You'll support impactful initiatives including pricing, packaging, multi-product strategies, and self-service approaches. You will collaborate cross-functionally with Engineering, Sales, Finance, Marketing, and Customer Relations to translate data needs into powerful solutions. You'll also establish best practices in analytics and mentor team members, ensuring high standards in data governance and insight generation. Your Mission: Partner with product and business leaders to define the analytics roadmap and deliver key projects in customer acquisition, engagement, and retention. Provide actionable insights and compelling narratives to influence major decisions at the C-level. Build a culture of experimentation by designing and executing rigorous A/B tests to measure business impact. Work closely with data engineers to continuously improve the data stack, governance practices, and analysis quality. A Little More About You: 5+ years of hands-on technical experience in a high growth environment. Proficiency in SQL for deriving insights. NEEDED Experience in building "Looker dashboards " in BI tools Proficiency in Python is a plus.

Job Title:Data ScientistExperience6-9 YearsLocation:Remote : Your Mission: Lead groundbreaking projects that leverage AI and machine learning techniques to optimize operations and drive business success. Take ownership of the entire lifecycle from model design, training, productionization, and incremental enhancement. Foster a culture of experimentation by designing and scaling rigorous A/B tests when needed to measure business impact. Educate internal analytics teams on current and emerging research, technologies, and best practices for leveraging ML and LLM in product design and development. Collaborate with AI Platform engineers to identify upcoming requirements and continuously evolve the AI platform offering. Establish best practices in data science and mentor future team members to maintain high standards in data governance and insight generation. Communicate effectively with stakeholders across various technical levels, articulating insights and recommendations about your solutions. Cultivate trust with stakeholders by consistently addressing their true fundamental needs and challenges. A Little More About You: 6+ years of data science, machine learning/statistical modeling experience. Experience implementing theoretical models in an applied environment. M.S. or Ph.D. in Statistics, Computer Science, Math, Operations Research, Physics, Economics, or other quantitative field. Strong interest in delivering data-driven solutions using ML and AI. Proficiency in data querying languages (e.g., SQL), scripting languages (e.g., Python), or statistical/mathematical software. Solid understanding of statistics, machine learning, operations research, and causal inference. Knowledge of NLP or Bayesian testing is a plus. Insatiable curiosity and bias toward action.

Job Title:C++ Quant DeveloperExperience12-15YearsLocationIndia/ US (Remote) : Description As a C++ Quant Developer, you will be responsible for implementing Treasury Futures and Options on Treasury Futures Models within BondCalc. You will collaborate with the Clients quants and ensure rigorous testing and validation of the models. Responsibilities: Implement Treasury Futures Model in C++ as per Clients Quant Library standards. Expand existing test suites and validate model accuracy. Collaborate with quantitative analysts to translate mathematical models into production-quality code. Optimize and modernize analytics infrastructure for fixed-income securities. Maintain version control and ensure code quality through rigorous testing. Skills & Qualifications: Proficiency in C++ with experience in financial libraries (e.g., QuantLib). Strong knowledge of fixed-income products, particularly Treasury Futures & Options. Experience with numerical computing, financial modeling, and Monte Carlo simulations. Ability to write clean, efficient, and testable code. Familiarity with Git, CI/CD, and Agile development methodologies. Experience working with quant teams in a high-performance computing environment. Project Overview The candidate will work on the Treasury Futures Model Development project, which involves C++ implementation of Treasury Futures Models in collaboration with quant teams. The role focuses on integrating these models into a Quant Library, enhancing analytics infrastructure, and conducting extensive testing. Required Qualifications Experience working in investment banking or asset management environments. Familiarity with quant libraries and financial engineering concepts. Proven track record of delivering large-scale quantitative development projects. FocusMathematical modeling and developing pricing/risk models. Key Responsibilities: Designing and implementing mathematical models for pricing financial derivatives. Developing risk models for portfolio management, VaR (Value-at-Risk), and stress testing. Writing C++ code to prototype and implement financial models. Calibrating models to market data and ensuring statistical robustness. Working closely with traders, portfolio managers, and quant developers to translate models into trading strategies. Applying stochastic calculus, numerical methods, and PDEs for pricing complex derivatives. Skills Required: Strong C++ & Python for model implementation and data analysis. Mathematics & FinanceStochastic processes, probability, linear algebra, and option pricing (Black-Scholes, Heston, SABR). Numerical MethodsMonte Carlo simulation, PDE solvers, finite difference methods (FDM), finite element methods (FEM). Data Science & Machine Learning (optional)Applying ML for signal detection in trading. Statistics & OptimizationKalman filtering, regression models, convex optimization. Common Employers: Investment banks (Barclays, Deutsche Bank, Credit Suisse) Hedge funds (AQR, Bridgewater, DE Shaw) Quantitative research firms (WorldQuant, Jane Street)

IT & Technology Senior Manager Data Analytics Company Background - GET provides skills and expertise to the Oil & Gas industry. - It provisions operational & supervisory field support, remote engineering, technical consulting and training services. Role And Responsibilities : - Work with stakeholders throughout the organization to identify opportunities for leveraging company data to drive business solutions. - Mine and analyze data from company databases to drive optimization and improvement of business strategies. - Assess the effectiveness and accuracy of data sources and data gathering techniques. - Develop custom data models and algorithms to apply to data sets. - Use predictive modelling to increase and optimize business outcomes. - Work individually or with extended teams to operationalize models & algorithms into structured software, programs or operational processes - Coordinate with different functional teams to implement models and monitor outcomes. - Develop processes and tools to monitor and analyze model performance and data accuracy. - Provide recommendations to business users based upon data/ model outcomes, and implement recommendations including changes in operational processes, technology or data management - Primary area of focus: PSCM/ VMI business; secondary area of focus: ICS KPI s - Business improvements pre & post (either operational program, algorithm, model or resultant software). Improvements measured in time and/or dollar savings - Satisfaction score of business users (of either operational program, algorithm, model or resultant software). Qualifications And Education Requirements - Graduate BSc/BTech in applied sciences with year 2 statistics courses. - Relevant Internship (at least 2 months) OR Relevant Certifications of Preferred Skills. Preferred Skills - Strong problem-solving skills with an emphasis on business development. - Experience the following coding languages : - R or python (Data Cleaning, Statistical and Modelling packages) , SQL, VBA and DAX (PowerBI) - Knowledge of working with and creating data architectures. - Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks. - Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests, and proper usage, etc.) and experience with applications. - Excellent written and verbal communication skills for coordinating across teams. - A drive to learn and master new technologies and technique Compliance Requirements : - GET has a Business Ethics Policy which provides guidance to all employees in their day-to-day roles as well as helping you and the business comply with the law at all times. The incumbent must read, understand and comply with, at all times, the policy along with all other corresponding policies, procedures and directives. QHSE Responsibilities - Demonstrate a personal commitment to Quality, Health, Safety and the Environment. - Apply GET, and where appropriate Client Company s, Quality, Health, Safety & Environment Policies and Safety Management Systems. - Promote a culture of continuous improvement, and lead by example to ensure company goals are achieved and exceeded. Skills - Analytical skills - Negotiation - Convincing skills Key Competencies - Never give up attitude - Flexible - Eye to detail Experience: Minimum 8 Years Of Experience

The Spec Analytics Intmd Analyst role is a developing professional position where you will independently handle most problems and have the freedom to solve complex issues. You will utilize your in-depth specialty knowledge along with industry standards to integrate with the team and achieve sub-function/job family objectives. Your role will involve applying analytical thinking and data analysis tools to make judgments and recommendations based on factual information with attention to detail. You will be dealing with variable issues that could have broader business impacts and will have a direct influence on the core activities of the business through close contact. Your communication and diplomacy skills will be crucial to exchange potentially complex information effectively. Responsibilities: - Working with large and complex data sets to evaluate, recommend, and support business strategies - Identifying and compiling data sets using tools like SQL and Access to predict, improve, and measure business outcomes - Documenting data requirements, data collection, processing, cleaning, and exploratory data analysis - Specializing in marketing, risk, digital, and AML fields - Assessing risk in business decisions with consideration for the firm's reputation and compliance with laws and regulations Skills and Experience: As a successful candidate, you should ideally have: - 5+ years of experience in data science, machine learning, or related fields - Advanced process management skills, detail-oriented, and organized - Curiosity and willingness to learn new skill sets, particularly in artificial intelligence - Strong programming skills in Python and proficiency in data science libraries such as scikit-learn, TensorFlow, PyTorch, and Transformers - Experience with statistical modeling techniques, data visualization tools, and GenAI solutions - Familiarity with agentic AI frameworks and MLOps Education: - Bachelors/University degree or equivalent experience This job description provides an overview of the work performed, and additional duties may be assigned as needed.,

At PwC, the focus in data and analytics is on leveraging data to drive insights and make informed business decisions. Utilizing advanced analytics techniques to help clients optimize their operations and achieve strategic goals is key. In data analysis at PwC, the emphasis is on utilizing advanced analytical techniques to extract insights from large datasets and drive data-driven decision-making. Skills in data manipulation, visualization, and statistical modeling play a crucial role in supporting clients in solving complex business problems. Candidates with 4+ years of hands-on experience are sought for the position of Senior Associate in supply chain analytics. Successful candidates should possess proven expertise in supply chain analytics across domains such as demand forecasting, inventory optimization, logistics, segmentation, and network design. Additionally, hands-on experience working on optimization methods like linear programming, mixed integer programming, and scheduling optimization is required. Proficiency in forecasting techniques and machine learning techniques, along with a strong command of statistical modeling, testing, and inference, is essential. Familiarity with GCP tools like BigQuery, Vertex AI, Dataflow, and Looker is also necessary. Required skills include building data pipelines and models for forecasting, optimization, and scenario planning, strong SQL and Python programming skills, experience deploying models in a GCP environment, and knowledge of orchestration tools like Cloud Composer (Airflow). Nice-to-have skills consist of familiarity with MLOps, containerization (Docker, Kubernetes), and orchestration tools, as well as strong communication and stakeholder engagement skills at the executive level. The roles and responsibilities of the Senior Associate involve assisting analytics projects within the supply chain domain, driving design, development, and delivery of data science solutions. They are expected to interact with and advise consultants/clients as subject matter experts, conduct analysis using advanced analytics tools, and implement quality control measures for deliverable integrity. Validating analysis outcomes, making presentations, and contributing to knowledge and firm building activities are also part of the role. The ideal candidate should hold a degree in BE / B.Tech / MCA / M.Sc / M.E / M.Tech / Masters Degree / MBA from a reputed institute.,

As a Data Science Associate Director at Accenture Strategy & Consulting, Global Network Data & AI practice in the Resources team, you will be part of a dynamic group that helps clients grow their businesses through analytics and insights. Your role will involve working closely with clients and stakeholders to drive business growth, identify new opportunities, and develop advanced analytics models for various client problems. Your responsibilities will include solution architecture, design, deployment, and monitoring of analytics models, as well as collaborating with internal teams to drive sales and innovation. You will be expected to lead a team of data analysts, work on large-scale datasets, and provide thought leadership in key capability areas such as tools & technology and asset development. Qualifications and Experience: - Bachelor's/Masters degree in Mathematics, Statistics, Computer Science, Computer Engineering, or related field - 15+ years of experience as a Data Science professional focusing on cloud services - Strong knowledge of Statistical Modeling, Machine Learning algorithms, and Experimental design - Expertise in experimental test design and the ability to derive business strategies from statistical findings - Experience in Utilities, Energy, Chemical, and Natural Resources industries preferred - Proficiency in programming languages like Python, PySpark, SQL, or Scala - Implementation of MLOps practices for streamlining machine learning lifecycle - Understanding of data integration, data modeling, and data warehousing concepts - Excellent analytical, problem-solving, communication, and collaboration skills - Relevant certifications in Azure Data Services or cloud data engineering are highly desirable If you are a strategic thinker with excellent communication skills, a passion for innovation, and a drive to make a difference in the world of data science, we invite you to join our team at Accenture Strategy & Consulting.,

As the Lead Data Scientist at Mastercard, you will have the opportunity to lead, mentor, and grow the data science team focused on developing production-grade services and capabilities. Your role will involve planning and directing data science and machine learning projects, designing and implementing machine learning models for various financial applications, and measuring, validating, implementing, monitoring, and improving the performance of both internal and external facing machine learning models. You will be expected to propose creative solutions to new challenges in the company, the financial industry, and data science, while effectively presenting technical problems and findings to business leaders and clients. Your responsibilities will also include leveraging best practices in machine learning and data engineering to develop scalable solutions, identifying areas where resources fall short of needs, and providing thoughtful and sustainable solutions to benefit the team. You should be a strong, confident, and excellent writer and speaker, capable of communicating your vision and roadmap effectively to a wide variety of stakeholders. To excel in this role, you should have at least 8 years of experience in data science and machine learning model development and deployments. Exposure to financial transactional structured and unstructured data, transaction classification, risk evaluation, and credit risk modeling is a plus. A strong understanding of NLP, Statistical Modeling, Visualization, and advanced Data Science techniques/methods is essential. Proficiency in SQL/Database operations is preferred, along with experience in technologies such as Kubernetes, Containers, Docker, REST APIs, Event Streams, and relevant tools like Tensorflow, Python, Sklearn, and Pandas. Moreover, you should have a strong desire to collaborate and come up with creative solutions, with additional experience in Finance and FinTech being beneficial. A Bachelors or Masters Degree in Computer Science, Information Technology, Engineering, Mathematics, or Statistics is preferred for this role. As part of Mastercard's corporate security responsibility, you will be expected to abide by the company's security policies and practices, ensure the confidentiality and integrity of accessed information, report any suspected information security violations or breaches, and complete all mandatory security trainings in accordance with Mastercard's guidelines. If you are passionate about leveraging data to provide high-quality customer solutions, possess strong technical leadership skills, and have an entrepreneurial mindset, then this Lead Data Scientist position at Mastercard could be the perfect opportunity for you to make a significant impact across various sectors of the economy.,

IT & Technology Senior Manager Data Analytics Company Background - GET provides skills and expertise to the Oil & Gas industry. - It provisions operational & supervisory field support, remote engineering, technical consulting and training services. Role And Responsibilities : - Work with stakeholders throughout the organization to identify opportunities for leveraging company data to drive business solutions. - Mine and analyze data from company databases to drive optimization and improvement of business strategies. - Assess the effectiveness and accuracy of data sources and data gathering techniques. - Develop custom data models and algorithms to apply to data sets. - Use predictive modelling to increase and optimize business outcomes. - Work individually or with extended teams to operationalize models & algorithms into structured software, programs or operational processes - Coordinate with different functional teams to implement models and monitor outcomes. - Develop processes and tools to monitor and analyze model performance and data accuracy. - Provide recommendations to business users based upon data/ model outcomes, and implement recommendations including changes in operational processes, technology or data management - Primary area of focus: PSCM/ VMI business; secondary area of focus: ICS KPI s - Business improvements pre & post (either operational program, algorithm, model or resultant software). Improvements measured in time and/or dollar savings - Satisfaction score of business users (of either operational program, algorithm, model or resultant software). Qualifications And Education Requirements - Graduate BSc/BTech in applied sciences with year 2 statistics courses. - Relevant Internship (at least 2 months) OR Relevant Certifications of Preferred Skills. Preferred Skills - Strong problem-solving skills with an emphasis on business development. - Experience the following coding languages : - R or python (Data Cleaning, Statistical and Modelling packages) , SQL, VBA and DAX (PowerBI) - Knowledge of working with and creating data architectures. - Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks. - Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests, and proper usage, etc.) and experience with applications. - Excellent written and verbal communication skills for coordinating across teams. - A drive to learn and master new technologies and technique Compliance Requirements : - GET has a Business Ethics Policy which provides guidance to all employees in their day-to-day roles as well as helping you and the business comply with the law at all times. The incumbent must read, understand and comply with, at all times, the policy along with all other corresponding policies, procedures and directives. QHSE Responsibilities - Demonstrate a personal commitment to Quality, Health, Safety and the Environment. - Apply GET, and where appropriate Client Company s, Quality, Health, Safety & Environment Policies and Safety Management Systems. - Promote a culture of continuous improvement, and lead by example to ensure company goals are achieved and exceeded. Skills - Analytical skills - Negotiation - Convincing skills Key Competencies - Never give up attitude - Flexible - Eye to detail Experience: Minimum 8 Years Of Experience

Role: Statistician (Data Science) Experience: 3 - 4 years Shift: 7.30 PM IST - 4.30 am IST (Night Shift) This requirement is for a Statistician with Python, SQL experience We are seeking a data-savvy Statistician to support analytics in the solar energy sector. This role involves using SQL to extract and analyze large datasets related to project performance, customer behavior, and operational efficiency. The ideal candidate will have a strong statistical foundation, practical experience with energy or engineering data, and the ability to translate insights into actionable strategies. Responsibilities: Analyze solar project flow and operational data using statistical methods such as Bayesian inference and distribution modeling, tailored to specific project characteristics. Write complex SQL queries for data extraction and analysis, & Explain them. Develop forecasts, trend analyses, and performance reports. Collaborate across teams to drive data-informed decisions. Ensure data accuracy and integrity through validation processes. Experience in applied Bayesian Statistics Minimum Qualifications: Bachelor's or Master's in Statistics, Data Science, (IEOR) industrial engineering and operations research, or related field. 3+ years of experience in a statistical/data analyst role. Strong proficiency in SQL. Effective communicator with strong data visualization skills. Preferred Qualifications: Python/ R Script preferred Knowledge of solar or energy industry data is a plus.

Company Overview We are looking for an innovative Lead AI/ML engineer to join our cutting-edge generative AI team. Our team develops a state-of-the-art gen-ai platform that creates domain-aware agents for financial operations, serving both internal processes and customer-facing products. We design and build scalable AI architectures and implement intelligent systems that operate within the complex world of finance. As a core part of Arcesiums technology innovation, we integrate our AI solutions into the firms broader financial technology ecosystem, driving efficiency, accuracy, and insights throughout the platform. What Youll Do: Design, develop, and implement complex AI/ML models and algorithms to solve business challenges Architect and build scalable AI/ML solutions using cloud technologies, particularly AWS Gather requirements, validate architecture, and create/review high-level and low-level designs for AI/ML projects Provide technical consultation on AI/ML technologies and solutions for various projects/products Create and review architectural decisions, ensuring the integration of AI/ML components with existing systems Ensure compliance of non-functional attributes (stability, scalability, performance, etc.) of AI/ML products to internal standards Guide and provide technical training on AI/ML topics, influencing business/technical decisions Own and execute AI/ML projects independently from an architectural standpoint Collaborate with cross-functional teams to integrate AI/ML solutions into production environments What Youll Need: Bachelors/Master s degree in computer science, Machine Learning, AI/ML 5+ years of relevant experience in AI/ML, with a strong background in Python, Java, or similar languages Experience with machine learning frameworks such as TensorFlow, PyTorch, or scikit-learn Proven track record in designing and implementing end-to-end ML pipelines for enterprise-grade software Strong knowledge of AI/ML algorithms, statistical modeling, and deep learning techniques Familiarity with AWS services, especially those related to AI/ML Experience with Infrastructure as Code tools, particularly Terraform Familiarity with Gen-AI Agentic frameworks like Langgraph, Experience with MLOps practices and tools for model deployment and monitoring Experience building and productionizing Python-based products Familiarity with SRE principles as they apply to AI/ML systems Knowledge of AI ethics and responsible AI practices Experience with natural language processing (NLP) or computer vision projects Contributions to open-source ML projects or research publications

Analyst/ Associate @ Acuity Knowledge Partners (2-4 years Model Risk Management) Key Responsibilities As part of the first line of defence, assess new and existing models for potential vulnerabilities, limitations, or misuse. Review, analyse and interpret findings and observations from the model validation team. Propose, implement and document required changes or enhancements to models, methodologies, data inputs, and assumption to address identified issues. Define and develop relevant edge case scenarios (e.g., extreme market, credit, or borrower conditions) to robustly challenge model performance Design and code analytical frameworks to simulate and test defined edge cases, ensuring comprehensive coverage of potential risk exposures. Execute edge case testing, systematically record results, and analyze model responses to assess robustness and identify weaknesses. Prepare detailed documentation of all analyses, code developed, and findings from edge case assessments, ensuring reproducibility and transparency. Organize and maintain supporting evidence for all remediated issues and edge case testing, facilitating future reviews, audits, and regulatory examinations. Desired Qualification Masters degree in mathematics, statistics, data science, finance or a relevant field. Experience in model development, model validation or model governance. Programming experience with demonstrated exposure to multiple languages such as Python, SAS, R, MATLAB, SQL, VBA, C++ or similar languages. Domain experience in Credit Risk, Market Risk, Operational Risk or relevant fields. Experience with vendor financial data vendors: Bloomberg, Refinitiv, CRSP, MSCI, Markit, S&P Capital IQ, etc. Solid understanding of financial predictive modeling, such as multi-factor risk models, time series forecasting, Value-At-Risk (VaR), optimization theory, and machine learning. Attainment or progress toward at least one of the following: Graduate degree in business or quantitative discipline, Chartered Financial Analyst (CFA) charter, FRM or PRM risk management certifications, Certified Investment Management Analyst (CIMA) certification. Demonstrated history of strong analytical skills and attention to detail.