Presales Consultant Ai

Why SoftwareOne?SoftwareOne is a leading global software and cloud solutions provider that is redefining how organizations build, buy, and manage everything in the cloud.By helping clients to migrate and modernize their workloads and applications – and in parallel, to navigate and optimize the resulting software and cloud changes – SoftwareOne unlocks the value of technology.The company's 9,200 employees are driven to deliver a portfolio of 7,500 software brands with sales and delivery capabilities in ninety countries.Headquartered in Switzerland, SoftwareOne is listed on the SIX Swiss Exchange under the ticker symbol SWON.Visit us at www.SoftwareOne.com The role As a Pre-Sales Consultant, you will be part of our sales team and you will play a crucial role in collaborating with our clients to understand their requirements, scope, and size opportunities effectively.Your primaryresponsibilities will revolve around providing technical support and translating customer requirements into tailored solutions to meet client needs, identifying opportunities for cross-selling and upselling, defining margins in alignment with both sales and delivery teams, drafting statements of work, and curating a repository of solution collaterals.Scoping and Sizing Opportunities Solution Design and Proposal Development Creation and Maintenance of Solution Collaterals Market Research and Insights Sales Support and Collaboration What we need to see from you Required Skills and Competencies: AI and Machine Learning: Strong understanding of machine learning algorithms, including supervised and unsupervised learning techniques.Ability to explain concepts such as regression, classification, clustering, and neural networks to clients with varying levels of technical expertise.Experience in applying AI and ML techniques to real-world problems across different domains such as healthcare, finance, retail, etc.Familiarity with deep learning frameworks such as TensorFlow, PyTorch, and Keras.Data Analysis and Visualization: Proficiency in data analysis tools like Python (NumPy, Pandas), R, and SQL for data manipulation and exploration.Experience in creating insightful data visualizations using libraries like Matplotlib, Seaborn, and Plotly to communicate findings effectively.Understanding of statistical methods and hypothesis testing for validating insights derived from data.Big Data Technologies: Knowledge of distributed computing frameworks like Hadoop, Spark, and Apache Flink for processing large-scale datasets.Understanding of NoSQL databases (MongoDB, Cassandra) and distributed storage systems (HDFS) for handling diverse data types and high-volume data streams.Data Engineering: Familiarity with ETL (Extract, Transform, Load) processes for data preparation and cleansing.Experience in data pipeline development using tools like Apache Airflow, Apache NiFi, or custom-built solutions.Ability to optimize data workflows for scalability, reliability, and performance.Cloud Computing: Proficiency in cloud platforms such as AWS, Azure, or Google Cloud Platform (GCP) for deploying and managing AI and data solutions.Understanding of cloud-based services like AWS SageMaker, Azure Machine Learning, and Google AI Platform for model training and deployment.AI Ethics and Bias Mitigation: Awareness of ethical considerations in AI development, including fairness, transparency, and accountability.Ability to identify and mitigate biases in datasets and AI models to ensure ethical use of AI technology.Domain Knowledge: Understanding of industry-specific challenges and opportunities related to AI and data, such as fraud detection in finance, predictive maintenance in manufacturing, or personalized recommendations in e-commerce.#LI-SH2 Job Function Field Sales Accommodations SoftwareOne welcomes applicants from all backgrounds and abilities to apply.If you require reasonable adjustments at any point during the recruitment process, email us at ****** include the role for which you are applying and your country location.Someone from our organization that is not part of the decision-making process will be in touch to discuss your specific needs and we will make every effort to accommodate you.Any information shared will be stored securely and treated in the strictest of confidence in line with GDPR.As a Pre-Sales Consultant, you will be part of our sales team and you will play a crucial role in collaborating with our clients to understand their requirements, scope, and size opportunities effectively.Your primaryresponsibilities will revolve around providing technical support and translating customer requirements into tailored solutions to meet client needs, identifying opportunities for cross-selling and upselling, defining margins in alignment with both sales and delivery teams, drafting statements of work, and curating a repository of solution collaterals.Scoping and Sizing Opportunities Solution Design and Proposal Development Creation and Maintenance of Solution Collaterals Market Research and Insights Sales Support and CollaborationRequired Skills and Competencies: AI and Machine Learning: Strong understanding of machine learning algorithms, including supervised and unsupervised learning techniques.Ability to explain concepts such as regression, classification, clustering, and neural networks to clients with varying levels of technical expertise.Experience in applying AI and ML techniques to real-world problems across different domains such as healthcare, finance, retail, etc.Familiarity with deep learning frameworks such as TensorFlow, PyTorch, and Keras.Data Analysis and Visualization: Proficiency in data analysis tools like Python (NumPy, Pandas), R, and SQL for data manipulation and exploration.Experience in creating insightful data visualizations using libraries like Matplotlib, Seaborn, and Plotly to communicate findings effectively.Understanding of statistical methods and hypothesis testing for validating insights derived from data.Big Data Technologies: Knowledge of distributed computing frameworks like Hadoop, Spark, and Apache Flink for processing large-scale datasets.Understanding of NoSQL databases (MongoDB, Cassandra) and distributed storage systems (HDFS) for handling diverse data types and high-volume data streams.Data Engineering: Familiarity with ETL (Extract, Transform, Load) processes for data preparation and cleansing.Experience in data pipeline development using tools like Apache Airflow, Apache NiFi, or custom-built solutions.Ability to optimize data workflows for scalability, reliability, and performance.Cloud Computing: Proficiency in cloud platforms such as AWS, Azure, or Google Cloud Platform (GCP) for deploying and managing AI and data solutions.Understanding of cloud-based services like AWS SageMaker, Azure Machine Learning, and Google AI Platform for model training and deployment.AI Ethics and Bias Mitigation: Awareness of ethical considerations in AI development, including fairness, transparency, and accountability.Ability to identify and mitigate biases in datasets and AI models to ensure ethical use of AI technology.Domain Knowledge: Understanding of industry-specific challenges and opportunities related to AI and data, such as fraud detection in finance, predictive maintenance in manufacturing, or personalized recommendations in e-commerce.#LI-SH2