Line Khachtban

Leadership • Define and drive the Data, Analytics & AI vision, shaping offers, positioning and roadmap across customers and internal stakeholders. • Own P&L, budget and economic models; lead pre-sales, executive pitching and RFPs. • Drive partnership strategy (Databricks) and operate in multi-client, multi-industry environments. ⸻ Team & People Management • Lead and coach ~20 data professionals, from juniors to senior Engineers, Architects and Tech Leads, including a management layer. • Recruit, onboard and develop data talents; drive certifications, skills growth and performance. • Manage staffing, sprint workload and capacity planning across engagements. ⸻ Business & Delivery • Achieved strong revenue growth through offer structuring, team scaling and partnerships. • Lead large-scale data programs for enterprise clients using hybrid delivery models (internal teams & independents). • Strong experience in T&M and Fixed-Price projects and data/cloud migration programs. ⸻ Data, Cloud & AI Expertise • Data Solution Architect on Azure Databricks, Microsoft Fabric, Snowflake & Cloud Azure, AWS and GCP products • Design enterprise-grade, interoperable data platforms and data hubs across geographies with high SLA and security constraints. • Architect and deploy AI platforms (AI agents, GenAI, ML & Deep Learning). • Define platform-oriented TOM and act as Technical Program Director. ⸻ Keywords #DataLeadership #HeadOfData #DataDirector #PracticeManager #Databricks #DataArchitecture #DataEngineering #DataAnalytics #AI #Azure #AWS #GCP #Snowflake #MicrosoftFabric #DataPlatform #P&L #BusinessGrowth #Presales #Partnerships #PeopleManagement #ProgramManagement #DigitalTransformation

- Develop agnostic machine learning framework (Scala, Spark) - Algorithms standardization (Scala, Spark) - Construction of Big Data infrastructure (Define business needs, Hdfs Architecture..) - Ensure good practices ( Big Data Mindset, Coding..) - Coaching Data scientist teams - Managing two trainees Keywords : Spark, GCP

- Processing and Analyzing data in a Large scale environment Hadoop Hortonworks. - Webtracking - Datavisualization. Keywords : Hortonworks, Hive, Qlikview

As a Webanalyst one of my main tasks was to establish customer journey and experience on Banque Accord’s Website. Based on webtracking, the aim of this task is to increase customer rationnalization, frame their web navigation and optimize customer experience. The first step was to identify poles with the most high level of trafic, furthermore I had to choose the most demanded custommer product and which has good Marketing flexibility. The financial product which fulfilled these conditions was “Virement +” , the product provides to the customer a usable amount of money at any time and repayable in monthly installments. The analysis of the customers viewed pages before subsribing to this product showed several customer journeys configurations and custommer profiles : From regular customer who borrows a direct path to more hesitant customer inquires. Plus, the establishment of a customer journey following the draw V + enabled me to detect potential product profiles which could interest a certain customer profil. Finally, one problem that arises is to adapt the client area given its risk profile, customer habits (used device,connexion time, draw amount...), plus his history on the Web but also in stores. So customers journey will be optimized as each customer will be driven the financial product that best fits their profile, increasing the ratio visits /draw of a certain financial products.

As a business statistical support my main tasks were to provide complete market/financial analysis in a short period of time. My missions were varied and multiple, these are some example of studies I had to produce : "​ Identifying factors that will lead to increase financial products sales/factors that increase anomalous contracts, activity monitoring, optimizing product penetration rate.." In a very autonomous way, I spent a lot of time in the data collection phase, Excel and Business object were my friends. Plus, I also had to work with colleges in different department thereby causing the development of my teamwork sense and resourcefulness. All the data gathered I had to audit their veracity (false data,data gap..), think about how to process with the data and finaly adjust them in the best way as to communicate with a no-statistician public.

Interested since always by the insurance field. I finally pulled out an internship at an Axa Agency. My first steps as an entity of the agency were not quiet satisfying because of the little knowledge I had in the insurance field. But risky as it was, I had nothing to loose, so I read books, asked questions and informed myself on the different contracts, type of clients and risks related to insuring companies. A bit later I was comfortable with different aspect of the insuring fiel, as for example insurance the basics and advance methods, customer interaction and detecting real customer needs.

Assisting a PhD on the Transports and Environment thematic. I had to gather, process and handle with a certain amount of information related to road transport as to compare it with other type of transports. Data had to be related with : - Environment Policy (Taxes, Subventions...) - Infrastructures costs - Environment impact - Innovative transports

Managed by an INSEE Analyst, the aim of this project was to establish a relationship between countries, different legislation, productivity, localisation, sectors and savoir faire of a product. A study based on price competitiveness, Tax system and product quality.