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Main Responsibilities Sales Performance Analysis Analyze sales by product, sales representative, territory/region, and customer segment. Identify trends, opportunities, and performance gaps. Track achievement against sales targets and budgets. Dashboard & Reporting Create and maintain dashboards for management. Prepare daily sales reports, weekly performance reviews, monthly business reviews, and forecast reports. Ensure data accuracy and consistency. Forecasting & Planning Support sales forecasting. Analyze historical sales trends. Predict future demand and revenue. Help management set realistic targets. Customer Analysis Analyze customer purchasing behavior. Identify high-value customers, customers at risk of leaving, and growth opportunities within accounts. Support customer segmentation strategies. Pricing & Profitability Analysis Analyze gross margins, product profitability, discount impact, and customer profitability. Recommend actions to improve profitability. CRM & Data Quality Management Monitor CRM data quality. Ensure opportunities, customer records, and sales activities are correctly recorded. Identify missing or inaccurate data. Business Intelligence Support Build reports using Microsoft Power BI, Tableau, Microsoft Excel, and SQL Server. Automate reporting processes where possible. Key KPIs for a Sales Data Analyst Report Accuracy % Dashboard Adoption Rate Forecast Accuracy % Data Quality Score Time Required to Generate Reports Number of Actionable Insights Implemented Revenue Opportunities Identified Margin Improvement Recommendations Requirements Qualifications – Sales Data Analyst Bachelor’s degree in Business Administration, Economics, Finance, Statistics, Data Analytics, Computer Science, or a related field. 5-7 years of experience in Sales Analysis, Business Intelligence, Data Analysis, Commercial Analytics, or a related role. Strong experience in sales performance analysis, forecasting, reporting, and business analytics. Advanced proficiency in Microsoft Excel, including Pivot Tables, Power Query, formulas, and data analysis. Hands-on experience with Microsoft Power BI and dashboard development. Good knowledge of SQL Server and the ability to extract, manipulate, and analyze data from databases. Knowledge of Tableau is an advantage. Strong understanding of sales KPIs, revenue, margins, targets, forecasting, and profitability analysis. Experience working with CRM systems and maintaining data accuracy and quality. Strong analytical and problem-solving skills with the ability to translate data into actionable business insights. Excellent attention to detail and ability to identify data discrepancies and performance gaps. Strong communication and presentation skills, with the ability to present complex data in a clear and management-friendly manner. Ability to work with large datasets and manage multiple reporting requirements within deadlines. Experience in the medical devices, pharmaceutical, FMCG, or distribution sectors is a plus. Show more

We are looking for Senior Data Analyst who has deep technical analytics with business partnership. In this role you aren't just expected to build dashboards, you're expected to own the entire analytical lifecycle and influence business decisions. What you'll do: Own analytics for one or more business domains (such as Lending, Payments, Risk, Sales, or Growth), acting as the primary analytics partner for stakeholders Translate ambiguous business questions into clear analytical problems, delivering actionable insights that drive decision-making Build, maintain, and govern trusted metrics and dashboards in Looker using LookML, ensuring consistent definitions and a reliable single source of truth Conduct advanced analyses, including funnel diagnostics, cohort analysis, segmentation, churn and activation analysis, and causal inference, to uncover not just what happened, but why Partner directly with senior stakeholders to scope requests, prioritize work, communicate findings, and confidently present analytical recommendations Ensure data quality by validating datasets, reconciling discrepancies, and identifying limitations related to data availability or privacy requirements Contribute to the analytics platform by improving documentation, semantic models, coding standards, and best practices that enable the team to scale Communicate insights through concise dashboards, presentations, and documentation tailored to different audiences To succeed in this role, you'll need to have: 5+ years of experience in data analytics, including at least 2 years operating independently in a senior individual contributor capacity Background in fintech or banking is strongly preferred Advanced SQL with strong understanding of complex datasets and multi-row relationships Experience with cloud data warehouses such as BigQuery (preferred), Snowflake, or Redshift Strong experience building governed BI solutions in Looker/LookML or comparable platforms such as Tableau or Power BI Experience with dbt or similar data transformation frameworks Working knowledge of Python or R for analysis and automation Strong foundation in statistics, experimentation, and causal analysis (A/B testing, cohort analysis, regression, diff-in-diff, regression discontinuity, etc.) Ability to transform ambiguous business questions into well-scoped analytical projects Strong analytical judgment and methodological rigor Excellent stakeholder management and communication skills Commitment to data quality, governance, and consistent metric definitions Ability to work autonomously and own projects from problem definition through delivery Show more

Position Summary: Linah is looking for a detail-oriented Data Analyst to turn raw agricultural field data into clear, actionable insight. The data analyst will be the bridge between what happens on client farms and the decisions made by both clients and Linah's technical support department — processing field metrics, building performance reports, flagging risks early, and quantifying the return on investment (ROI) of Linah's interventions Job Duties & Responsibilities: Build and maintain the "Historical Farm Profile" database, ensuring all data from field engineers and lab results are accurately and consistently recorded Collect, clean, and validate agricultural data gathered from client farms (yield, soil health, irrigation, inputs usage, weather, crop cycles, etc.) Process and structure raw field data into usable datasets for analysis Calculate cost vs. yield metrics, tracking how Linah's interventions impact the client's bottom line Calculate and track the broader ROI of Linah's interventions (e.g., input recommendations, technology adoption, training programs) against baseline performance Prepare the data that feeds into the Client Digital Dashboard, including implementation rates and technical program progress Build dashboards and visualizations that clearly communicate farm performance trends over time Analyze trends across different regions to provide the R&D and Technical teams with early warnings about pest outbreaks or climate impacts Design and generate the standardized, logic-based technical reports delivered to clients Prepare regular performance reports for clients and internal management, translating technical data into plain-language insights Collaborate with field agronomists/engineers to ensure data collected is accurate, complete, and relevant Maintain data quality standards and documentation for all datasets, databases, and reporting processes Support management with ad hoc data requests and predictive analysis for planning and forecasting Continuously improve reporting templates, dashboards, and analytical methods based on client and management feedback Requirements Bachelor's degree in Data Science, Statistics, Agricultural Economics, Agronomy, Computer Science, or a related field 3+ years of experience in data analysis, ideally within agriculture, agtech, or FMCG, or supply chain sectors Strong proficiency in Excel and at least one analytics/BI tool (e.g., Power BI, Tableau, Looker) Working knowledge of SQL for data querying, database maintenance, and manipulation Experience with Python or R for data processing/analysis is a plus Ability to build clear, digestible dashboards and reports for both technical teams and non-technical audiences Strong understanding of basic agricultural concepts (crop cycles, yield metrics, farm inputs) or willingness to learn quickly Excellent analytical thinking and attention to detail Strong communication skills — able to translate numbers into a story for clients and management Benefits Job location: Baharia Oasis Medical insurance Social insurance Bonus upon company policy Show more

About this Position The Cloud Engineer supports the development and operation of Henkel's enterprise multi-cloud platform environment, covering Microsoft Azure and Google Cloud Platform. The role focuses on building scalable cloud infrastructure, automation, and platform engineering solutions that support a centralized ecosystem serving global application teams and business units. As part of a hands-on engineering environment within Henkel's Cloud Organization, the position contributes to infrastructure engineering, cloud-native capabilities, and platform self-service that strengthen how enterprise solutions are deployed and scaled across Henkel. What You´ll Do Design, build, and optimize cloud infrastructure on Microsoft Azure and Google Cloud Platform, including compute, networking, IAM, and storage services. Develop and maintain infrastructure automation solutions using Terraform and Ansible following Infrastructure as Code (IaC) practices. Build and maintain CI/CD deployment pipelines supporting reliable multi-environment platform delivery and GitOps workflows. Support the provisioning and lifecycle management of cloud projects and resources such as VPCs, service accounts, landing zones, and platform blueprints. Contribute to the team's Internal Developer Platform (IDP) initiative by engineering self-service capabilities and reusable platform blueprints for application teams. Support API and agent gateway design, including model routing and FinOps tracking for LLM token consumption. Support platform security, identity management, and compliance capabilities across cloud-native environments. Collaborate with global and cross-functional teams including Platform Owners globally to deliver scalable and reliable enterprise platform solutions. Participate in disaster recovery planning and execution. Optimize cloud-based solutions and infrastructure as part of the company's digital strategy. Contribute to the development of best practices and documentation for IT operations. What makes you a good fit 2–3 years of hands-on experience in cloud engineering or DevOps roles Solid working knowledge of GCP or Azure - compute, networking, IAM, and storage fundamentals; experience with both is a plus. Hands on experince with infrastructure-as-code practices, preferably Terraform; Ansible is an advantage. Experience building and maintaining CI/CD pipelines and multi-environment deployment workflows. Familiarity with Linux environments, shell scripting (Bash), and container-based workloads. Understanding of Kubernetes or OpenShift and GitOps practices is an advantage. Basic familiarity with AI/LLM APIs such as Azure OpenAI or Vertex AI; hands-on experience is a strong plus. Experience with API gateway solutions (Azure APIM, Apigee, or similar) is a plus. Scripting experience with Python is considered a plus. Strong analytical, problem-solving, and communication skills. Ability to work independently and collaborate effectively across distributed, cross-functional teams. Proactive mindset with a passion for automation, engineering quality, and continuously learning new technologies. Some perks of joining Henkel Flexible work scheme with flexible hours, hybrid work model, and work from anywhere policy for up to 30 days per year Diverse national and international growth opportunities Global wellbeing standards with health and preventive care programs Gender-neutral parental leave for a minimum of 8 weeks Employee Share Plan with voluntary investment and Henkel matching shares Comprehensive Health Insurance for employee + dependents Employee Assistance Programme provides a wide range of mental health and wellbeing benefits At Henkel, we come from a broad range of backgrounds, perspectives, and life experiences. We believe the uniqueness of all our employees is the power in us. Become part of the team and bring your uniqueness to us! We look for a diverse team of individuals who possess different backgrounds, experiences, personalities and mindsets. Show more

We are hiring a Senior Data Scientist to join our team at Klivvr. What you'll do: Own a domain such as credit, risk, or growth end to end, setting the modeling strategy and being accountable for the systems that result Take on the most ambiguous, highest-stakes problems, including framing what should be built and why before any modeling begins Make and defend the hard technical calls, choosing the simplest approach that solves the problem rather than the most sophisticated one Drive models into production and own their long-term health, performance, and reliability once they're live Set technical direction and standards that other data scientists build on, through design reviews, shared tooling, and engineering practices Mentor data scientists across levels and raise the quality bar for the team's work Translate business strategy into a coherent data science roadmap and communicate tradeoffs clearly to leadership To succeed in this role, you'll need to have: 5+ years of hands-on data science or applied ML experience, with a track record of owning systems in production end to end Deep proficiency in Python (NumPy, pandas, scikit-learn) and SQL, and strong software engineering fundamentals Strong grounding in statistics, probability, and machine learning, with the judgment to know which method actually fits the problem Experience designing and operating large-scale ML systems on cloud platforms (AWS preferred) A demonstrated ability to lead ambiguous, cross-functional initiatives without close guidance Excellent communication skills, including the ability to influence technical and business stakeholders and to make others better through your feedback Show more

We are looking for a Senior AI Engineer with over 4 years of experience to lead our AI initiatives. In this role, you will be responsible for driving the design, development, and deployment of cutting-edge AI solutions. You will provide technical leadership to a team of AI engineers, mentor junior team members, and collaborate closely with stakeholders to deliver impactful AI-driven products. This position requires deep expertise in machine learning, data engineering, and software development practices. Responsibilities: Lead the end-to-end development of AI models Architect scalable AI systems and infrastructure to support large-scale data processing and model training Mentor and coach junior AI engineers, fostering a culture of continuous learning and technical excellence Collaborate with product managers and business stakeholders to define AI strategy and roadmap Conduct research and stay abreast of advancements in AI/ML fields to drive innovation Ensure robustness, scalability, and performance of AI solutions in production environments Requirements Requirements Bachelor's or Master's. in Computer Science, Engineering, or a related field. 4+ years of experience in AI, machine learning, or data science roles, with a proven track record of delivering complex projects Proven experience designing and deploying Generative AI (GenAI) systems using large language models (LLMs) Expertise in Python, TensorFlow, PyTorch, or other ML frameworks Strong knowledge of distributed computing, data engineering, and cloud platforms Hands-on experience with RAG architectures, vector search engines, and embedding models Deep experience with prompt engineering and LLM fine-tuning Experience building intelligent agent-based systems using frameworks like LangChain, LangGraph, or CrewAI Familiarity with LLM evaluation, observability, and cost/performance optimization Hands-on experience with cloud platforms such as AWS, Azure, or Google Cloud Excellent leadership, communication, and stakeholder management skills Preferred Qualifications:. Experience working with multi-agent architectures, planning/execution agents, or tool-using LLMs Contributions to open-source GenAI projects, or participation in applied research involving LLMs, embeddings, or agentic reasoning Show more