37 Predictive Modelling Jobs - Page 2

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

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

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

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

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

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

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

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

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

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

We will count on you to: Contribute to developing an inclusive work environment that respects and values differences of background, experience, and thought. Organize client data, check data for reasonability, load data into predictive models, run the models, share insights with senior colleagues, and compile coherent and compelling narratives to help clients understand their degree of risk. Perform basic calculations with client data to assess a range of risk exposures and predict outcomes for clients in support of reinsurance transaction process. Conduct research on industry/regulatory developments that affect loss liabilities to determine the impact on clients. Generating multiple exhibits, dashboards and decks leading to have impactful and insightful discussions with clients on their reinsurance strategy. Establish and maintain strong relationships with brokers/clients/reinsurers/colleagues, assist in promptly responding to client queries and concerns. Keep teams updated on industry-specific and specialty related trends that may affect reinsurance programs/calculations. Leverage our proprietary MetaRisk software suite and other internal tools to develop and optimize bespoke reinsurance transactions and evaluate their impact on our clients capital, growth, and volatility objectives. What you need to have: Bachelors or masters degree in a technical discipline such as Actuarial Science, Data Science, Engineering, Physics, Mathematics or Statistics. 2-4 years of work experience; completion of at least 2 actuarial exams preferred. Curious and proactive mindset: desire and ability to lead internal initiatives and research projects to completion. A collaborative, team-oriented mindset and effective interpersonal skills that is a positive and helpful presence in colleague and client interactions. Strong ability to be organized and detail oriented. Capacity to progress multiple projects at the same time. A desire and ability to grow beyond your current capabilities. Superior communication and presentation skills. Proficient in MS Excel with skills in other MS Office products. What makes you stand out: Familiarity with programming languages & visualization tools (i.e., R, Python, SQL, Alteryx, Power BI). Experience in a technical role at a reinsurance broker, market, or catastrophe model vendor. Prior experience in relevant re/insurance field. Understanding of the reinsurance industry and product lines.

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