Data Engineer

Data Scientist- AI Architect

ASC - Downstream Data Scientist

Data Science Manager

Machine Learning Scientist

Techno-Economic Modeling Specialist

Senior Data Engineer

ASC - Business Sys Analyst I (AI)

Responsibilities: <ul><li>Design and implement scalable data pipelines and data warehouse solutions using Informatica PowerCenter.</li><li>Develop ETL processes to ingest data from various sources into the data warehouse.</li><li>Optimize and tune SQL queries for performance improvements.</li><li>Collaborate with cross-functional teams (e.g., Data Scientists, Analysts, Software Engineers) to understand data requirements and deliver solutions.</li><li>Ability to understand and integrate data sources based on different technologies like Streaming Data, Change Data Capture, APIs , Message Queues, Semi-structured(JSON,XML) and unstructured data.</li><li>Analyze raw data to determine optimal solutions for data processing and ingestions</li><li>Implement data quality and validation processes to ensure high data integrity and reliability.</li><li>Monitor and troubleshoot data pipeline issues and implement solutions in a timely manner.</li><li>Document technical designs, data mappings, and configuration management processes.</li></ul> Requirements: <ul><li>Bachelor’s degree in Computer Science, Engineering, or a related field.</li><li>3-4 years of hands-on experience in data engineering roles.</li><li>Proficiency in Informatica Informatica IICS (ECDI, CDI CAI, Mass Ingestion etc) for designing and developing ETL workflows.</li><li>Strong SQL programming skills with experience in optimizing queries and database performance.</li><li>Experience working with large-scale data warehousing and data modeling concepts.</li><li>Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and their data services is a plus.</li><li>Excellent problem-solving skills and ability to work independently as well as part of a team.</li><li>Strong communication skills and ability to collaborate effectively across teams.</li></ul>

Responsibilities: As part of the Data Science organization at our client, the Generative AI team is working on digital transformation.We are developing enterprise solutions for Commercial, Technology and Operations functions. As an AI Engineer you will lead the design, development and adoption of new technology and analytics, help contribute to our AI strategy, and partner with leaders across the company.The role will involve collaborating with cross-functional teams to ensure the successful creation and roll-out of AI driven solutions.Role Type : Individual Contributor As AI Engineers you will perform work including: Design, develop, and implement systems leveraging Large Language Models (LLMs) for various applications.Prepare data, fine-tune models, and build data, analytics and ML Pipelines to support AI applicationsPerform statistical analysis and data manipulation using language models.Collaborate with business partners and key stakeholders to understand their needs and present insights and solutions.Architect and design innovative AI solutions tailored to business requirements.Utilize cloud technologies in Azure and/or AWS for deploying and managing AI models and solutions.Communicate complex technical concepts and results to non-technical audiences effectively.Contribute to the development of AI strategies and governance for the organization.Stay current with advancements in AI and machine learning technologies and apply them to solve business challenges.Lead efforts to improve enterprise adoption and proficiency in the use of AI tools Requirements:10+ years of experience in data science, AI, or a related field preferred.Proficiency in software development and statistical analysis.Experience with Large Language Models and their applications.Strong communication skills and the ability to present technical results to business stakeholders.Experience with solution architecting and design preferred.Hands-on experience with cloud platforms such as Azure and/or AWS.Proficiency in programming languages such as Python, R, or similar.Strong problem-solving skills and the ability to work independently as well as part of a team.Bachelor's in Computer Science, Mathematics, Statistics, or a similar field. Master's or Ph.D. preferred.Preferred Qualifications: Experience with large language models and supporting workflows.History of project leadership and development.Familiarity with Agile development.Experience in applications related to sales, marketing, and market research a plus. 

Responsibilities:Formulate and lead multifaceted analytic studies against large volumes of data.Interpret and analyze data using exploratory mathematic and statistical techniques based on the scientific method.Coordinate research and analytic activities utilizing various data points (unstructured and structured) and employ programming to clean, massage, and organize the data.Experiment against data points, provide information based on experiment results and provide previously undiscovered solutions to command data challenges.Lead all data experiments tasked by the Data Science Team.Coordinate with Data Engineers to build data environments providing data identified by Data Analysts, Data Integrators, Knowledge Managers, and Intel Analysts.Develop methodology and processes for prioritization and scheduling of projects.Analyze problems and determine root causes.Define company data assets (data models), spark, sparkSQL, and hiveSQL jobs to populate data models.Work closely with all business units and engineering teams to develop strategy for long term data platform architecture.Requirements:As the successful candidate you will hold a Bachelor degree in Operations Research, Industrial Engineering, Applied Mathematics, Statistics, Physics, Computer Science, or related fields. An advanced degree is preferred.You will have 5-7 years of professional experience in related fieldYou will have Proficiency with one or more programming languages (Java, C++, Python, R, etc.)You will be able to demonstrate experience applying data science methods to real-world data problemsYou will also have experience in utilizing visualization tools to take advantage of the growing volume of available information

Purpose of Job Role:work with a Analytics team (in the Front - business line) and will have the primary responsibility for generating data products (reports, applications) to meet business needscollaborate as part of a cross functional team with business departments (Commercial, Marketing, Strategy, etc.) and IT (data engineering)support stakeholders in choosing the best approach to achieve business goals with data insights, reporting and data models; always having in mind how these teams will use, consume or interact with the data productspartner with IT to secure data models are built leveraging best practices and ensuring KPI automationlead Data scientists team and support the designing of different solutions: best-in-class visualization, hypothesis testing (A/B testing), advanced models and algorithms deploymentsThe successful candidate should be able to think/act strategically, develop structured and well designed data processes to fully connect the flow from back to front, being able to understand business needs and prioritize/align requirements to the business and Analytics strategy; he will also play a role model within Analytics team.Responsibilities:Develop strategical reports and dashboards with a Proof of Value and scalability approachDevelop and implement data products for main stakeholders (Commercial, Marketing, Finance departments)Work as a translator between business and IT departments for KPIs definition and automation. Coordinate user-focused documentation for the data solutionsCollaborate with architects from the IT department to support data governance and quality effortsSupport requests prioritization to align workload to business strategyCoordinate and develop teams of Data ScientistsCommunicate insights, data products and reports status and results clearly to the partnersNegotiate requests, workloads and team assignment with different partnersRequirements:Bachelor’s degree in Mathematics, Actuary, Economy, Engineering, Computer scienceMaster's degree in Data Science, Computer Science, Statistics or related area is a plus5+ years’ proven experience working on Data Visualization, Data Science, Machine LearningAdvanced experience with programming languages for data modeling (SQL, R, Python)Advanced experience working with Business Intelligence platforms and tools (Microsoft Power BI)Experience with Matillion is a plusProject Management & communication skillsProblem solving/critical thinking mindsetHighly organizedData storytelling and communication skillsProficiency in English

Role Description:As an ML engineer, you will have the opportunity to work on large-scale ranking and recommendation systems for sequential content consumption on newly installed user interface designs The solutions developed by you will aid in building novel and meaningful graph-based community assets around the network of consumers and merchants, to ultimately drive key product and marketing KPIs associated with customer experience, engagement and the revenue bottom line.Responsibilities: As a Machine Learning Scientist you will be responsible for:Creating innovative AI/ML solutions that enhance personalization for users, with a focus on ranking and recommendation algorithms.Writing scalable, production-quality code to deploy models on company infrastructure, optimizing for performance and efficiency.Collaborating with cross-functional teams, including engineering, product, and marketing, to design, develop, and track key performance indicators (KPIs) for ranking and recommendation models.Conducting experiments to measure these KPIs, as well as deriving actionable insights from the data, to continually improve the technology and drive business outcomes.Requirements:Advanced degree (MS or PhD) in quantitative science or engineering field (for example: Computer Science, Statistics, Mathematics, Operation Research) with a minimum of 2 years of hands-on experience for MS as an individual contributor.Proven expertise in designing and developing AI/ML models for ranking and recommendation systems, with in-depth understanding of both traditional collaborative/content-based recommendation methods and cutting-edge deep learning algorithms, reinforcement learning, and bandit techniques.Demonstrated ability to write scalable high quality code in Python, Java, Scala or a similar programming language, and to design and implement data engineering pipelines using technologies like Hive, SQL, BigQuery, or Spark.Proficiency in machine learning frameworks and packages, such as Tensorflow and PyTorch. 

Responsibilities:Support strategic option analysis (e.g., make vs. buy, technology portfolio prioritization) via provision of cost-benefit assessments and analysis, as well as validation of economic and risk assumptions; present findings and recommendations based on analysis to senior management.Analyze trends and market intelligence to support the development of business cases (and value hypothesis) for technology projects going through the corporate technology stage-gate process.Create financial models and establish the value of technologies for potential commercial applications, in support of technology development, deployment and external licensing efforts. Support technology project teams in the development of a robust financial case for internally developed technologies, including techno-economic models for investment appraisal of technologies in the stage-gate process.Provide detailed financial and economic insights for evaluating technology project performance by analyzing relevant data against the technology scorecard KPIs.Support technology development, demonstration, internal deployment and external commercialization opportunities, including implementation of robust deployment plans. This includes tracking and accurately reporting the value realized from deployed technologies, as well as supporting internal and external reviews of the relevant financials.Provide input to help evaluate licensing opportunities to enable favorable license terms.Develop, manage and assure the quality of economic modelling tools used within TOC.Periodically review and improve financial models, maintain and update the repository of licenses and portfolio position on all approved technology/innovation applications.Work flexibly across TOC and/or R&D domains as required.Share and transfer techno-economic evaluation fundamentals knowledge to increase financial acumen in the organization. Requirements:Bachelor’s degree in Economics, Econometrics, Engineering, Statistics, Business Administration, or a related discipline. An advanced degree (MBA/Finance) is highly preferred.At least 15 years of professional experience, including a minimum of: 10 years in leading organizations in the energy or chemicals sector, and/or with leading management consulting firm(s); and five years’ conducting incremental, cost-benefit/effectiveness and budget impact analyses using mathematical, economic or statistical modelling tools and techniques, such as decision tree analysis, Markov modelling, and/or discrete event simulations, including Monte Carlo simulations and real options, risk adjustment, and risk management.In-depth knowledge and understanding of one or more relevant core businesses (downstream refining, petrochemicals, midstream, and upstream) and emerging technologies related to corporate sustainability (Circular carbon economy; CO2 capture, utilization and storage; nonmetallic materials; sustainable plastics; artificial intelligence; and industrial sensoring and monitoring).Ability to develop insights from market research to technology business case development; mastery in quantitative economic and financial analysis, portfolio modelling and technology valuation, including: incremental, risk-adjusted, cost-benefit, variance and scenario analyses, NPV, and sensitivity analysis, using a range of tools and applications (Microsoft Excel, SQL, SAS, R, MatLab, Tableau, and/or other VBA type software to analyze complex and large data sets, Planisware, or similar tools for portfolio and project management)

Responsibilities:Data engineers need to write code to develop, maintain, and optimize data pipelines, as well as to implement data storage solutions and data processing systems. They typically use programming languages such as Python, Java, or Scala, along with big data technologies like Hadoop, Spark, and KafkaDesigning scalable data architecture that supports both transactional and analytical workloads. This involves understanding business requirements and translating them into technical solutions.Developing robust data pipelines to ingest, cleanse, transform, and aggregate data from various sources (internal and external). This includes both batch and real-time/streaming data processing.Integrating data from disparate sources and ensuring data consistency, integrity, and reliability across different systems.Requirements:5-8 years experience with GCP, Big Query, Data Fusion, Analytics Hub and DataFlowExperience leading othersExperience managing projectsExcellent written and verbal communication skillsTime ManagementAbility to work alone and with a teamAbility to mentor junior membersA Bachelor’s degree in MIS or mathematics, statistics, or computer science, international equivalent, or equivalent job experience

Responsibilities:Create automations that take data through the ETL (extract, transform, load) process, both for normal reporting and advanced analytics modelsCreate and maintain Azure Pipelines that ensure the transfer of data between different usesManagement of internal databasesProfiling Azure data setsData modeling using Azure platform toolsBuilding data architecture in AzureWorking with SQL databases for data extractionUsing Power BI to expose data to end usersCreating reports in Power BI according to business needsSupporting the business in their processesCollecting information and ensuring its accuracyRequirements:English language - advanced levelPC operating knowledge (MS Office) - advanced levelAnticipation, planning and strategic thinking skillsAnalysis and synthesis skillsGood at connecting and communicating with business to understand their needs and integrate in the solutions providedGrowth mindset and willing to developAzure DevOps AdvancedAdvanced SQLPower BI notes (nice to have)Python for Data Science (desirable)Statistics notes (nice to have)

Responsibilities:Formulates and leads guided, multifaceted analytic studies against large volumes of data.Interprets and analyzes data using exploratory mathematic and statistical techniques based on the scientific method.Coordinates research and analytic activities utilizing various data points (unstructured and structured) and employ programming to clean, massage, and organize the data.Experiments against data points, provide information based on experiment results and provide previously undiscovered solutions to command data challenges.Leads all data experiments tasked by the Data Science Team.Coordinates with Data Engineers to build data environments providing data identified by Data Analysts, Data Integrators, Knowledge Managers, and Intel Analysts.Develops methodology and processes for prioritization and scheduling of projects.Analyzes problems and determines root causes.Defines company data assets (data models), spark, sparkSQL, and hiveSQL jobs to populate data models.Works closely with all business units and engineering teams to develop strategy for long term data platform architecture.Requirements:Master’s degree in Operations Research, Industrial Engineering, Applied Mathematics, Statistics, Physics, Computer Science, or related fields5-7 years of professional experienceProficient with one or more programming languages (Java, C++, Python, R, etc.)Demonstrated experience applying data science methods to real-world data problemsExperience utilizing visualization tools to take advantage of the growing volume of available informationData Scientist Qualifications / Skills:Advanced analytical knowledge of dataConducting big data analysisData conditioningProgramming advanced computingDeveloping algorithmsDeveloping software and data modelsExecuting predictive analytics

Responsibilities:Design, develop, and implement AI-powered solutions to automate manual tasks, optimize processes, and enhance data-driven decision-making in Financial Accounting, Treasury, Performance management and Investor Relations.Work closely with business stakeholders to understand their needs, translate them into technical requirements, and deliver impactful solutions. Assess requirements related to Finance AI uses cases; Perform option evaluation; Provide support for implementation.Develop and maintain machine learning models for tasks such as financial forecasting, fraud detection, anomaly detection, risk assessment, and investor sentiment analysis.Clean, transform, and analyze large datasets from various sources to ensure data quality and prepare it for modeling.Stay up-to-date on the latest advancements in AI and machine learning, identify potential applications for the finance function, and propose relevant pilot projects.Communicate technical concepts and findings effectively to both technical and non-technical audiences.Participate in cross-functional initiatives to integrate AI and data science into broader business transformation efforts.Organize and facilitate workshops with different users and consultants to document processes and drive transformation.Lead the delivery and execution of key digital initiatives.Participate in solutions development through projects and programs, collaborating with business and technology groups.Maintain, support and optimize digital solutions.Requirements:As the successful candidate you will hold a Bachelor’s degree in Engineering, Computer Science, Mathematics, Statistics or IT from a recognized and approved program. Possession of an advanced business degree (e.g. MBA) and/or relevant professional certification (e.g. CMA, CFA, CPA) is preferred but not required. You will have six to eight years’ experience in Data Science, Artificial Intelligence and other related advanced analytics implementation of financial systems.Expertise in Python programming languages and libraries such as NumPy, pandas, scikit-learn, TensorFlow, or PyTorch is required. UI programming, such as with React, is requiredSkills to leverage Google Cloud or Azure Cloud for advanced analytics is desirable.You will be able to demonstrate a thorough understanding of the various aspects of implementing AI systems in Finance including articulation and measurement of benefits, evaluation of technical and execution options, critical success factors, and project risks.You must have project experience implementing AI solutions and will be able to analyze the business requirements, evaluate and recommend technical options and support the execution process for implementing such solutions.Ability to get involved in hands on technical solution management is preferred. 

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21 statistics Jobs found

Data Engineer

Data Scientist- AI Architect

ASC - Downstream Data Scientist

Data Science Manager

Machine Learning Scientist

Techno-Economic Modeling Specialist

Senior Data Engineer

Data Engineer

ASC - Downstream Data Scientist

ASC - Business Sys Analyst I (AI)

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Data Engineer

Data Scientist- AI Architect

ASC - Downstream Data Scientist

Data Science Manager

Machine Learning Scientist

Techno-Economic Modeling Specialist

Senior Data Engineer

Data Engineer

ASC - Downstream Data Scientist

ASC - Business Sys Analyst I (AI)

WhiteCrow WhiteCrow is on a mission to connect companies with the best talent across the globe.

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WhiteCrow is on a mission to connect companies with the best talent across the globe.