Data Scientist

Do you want to boost your career and collaborate with expert, talented colleagues to solve and deliver against our clients most important challenges? We are growing and are looking for people to join our team. Youll be part of an entrepreneurial, highgrowth environment of 300.000 employees. Our dynamic organization allows you to work across functional business pillars, contributing your ideas, experiences, diverse thinking, and a strong mindset. Are you ready?

Job Overview:

We are looking for a highly skilled Data Scientist to join our team. As a Data Scientist, you will be responsible for analysing large amounts of raw data to extract valuable insights, building machine learning models, and contributing to datadriven decisionmaking processes across the organisation. You will work closely with crossfunctional teams, including data engineers, analysts, and business stakeholders, to turn data into actionable strategies that drive business outcomes.

The ideal candidate should have a strong background in statistical analysis, machine learning, and data mining techniques, and should be capable of translating complex datasets into understandable insights that impact business growth.

Key Responsibilities:

1. Data Analysis and Exploration:
2. • Analyse large, complex datasets to identify trends, patterns, and insights that inform business decisions.
   • • Use statistical methods to explore and interpret data, providing actionable recommendations to stakeholders.
     • • Identify and address data quality issues, ensuring accurate and consistent analyses.
       • 1. Machine Learning and Predictive Modelling:
         2. • Build, test, and deploy predictive models and machine learning algorithms to solve business problems (e.g., customer segmentation, demand forecasting, recommendation systems).
            • • Continuously improve models by retraining and optimising based on performance metrics and feedback.
              • • Collaborate with data engineers to integrate models into production systems for realtime decisionmaking.
                • 1. Business ProblemSolving:
                  2. • Work with business teams to define key problems and translate business objectives into data science projects.
                     • • Develop hypotheses and design experiments to test various business scenarios using datadriven approaches.
                       • • Present datadriven insights and recommendations to both technical and nontechnical stakeholders.
                         • 1. Data Visualisation and Reporting:
                           2. • Create clear and compelling data visualisations to communicate findings (using tools like Tableau, Power BI, or matplotlibSeaborn).
                              • • Design and generate dashboards and reports to help business teams track key metrics and KPIs.
                                • • Explain complex analytical results in a clear, concise, and actionable manner to stakeholders at all levels.
                                  • 1. Data Wrangling and Preparation:
                                    2. • Extract, clean, and prepare data from various internal and external sources for analysis and modelling.
                                       • • Perform data transformations, feature engineering, and scaling to optimise model performance.
                                         • • Collaborate with data engineers to design data pipelines that ensure the availability of clean, structured, and highquality data.
                                           • 1. Statistical and Mathematical Modelling:
                                             2. • Apply advanced statistical techniques, such as hypothesis testing, regression analysis, classification, and clustering, to derive insights and build models.
                                                • • Perform AB testing, multivariate testing, and other forms of experimental design to measure the effectiveness of business interventions.
                                                  • 1. Collaboration and Stakeholder Management:
                                                    2. • Work closely with business leaders, product teams, and other stakeholders to understand their data needs and provide them with insights that drive strategy.
                                                       • • Collaborate with data engineers, analysts, and software developers to implement data solutions that align with business goals.
                                                         • • Support continuous learning and knowledge sharing by presenting findings and methodologies to colleagues.

                                                           • Requirements

                                                             Skills and Qualifications:

                                                             Essential Skills:

                                                             • Bachelor’s or Master’s degree in Data Science, Statistics, Mathematics, Computer Science, Engineering, or a related field. A Ph.D. is a plus.
                                                             • • Proven experience (3+ years) as a Data Scientist, Machine Learning Engineer, or similar role.
                                                               • • Strong proficiency in programming languages such as Python or R for data analysis, with experience in libraries like pandas, NumPy, scikitlearn, and TensorFlowPyTorch.
                                                                 • • Solid understanding of statistical analysis and experience in applying techniques like regression, hypothesis testing, and multivariate analysis.
                                                                   • • Handson experience with machine learning algorithms (classification, clustering, regression, deep learning).
                                                                     • • Proficiency with SQL for querying large datasets and relational databases.
                                                                       • • Familiarity with data visualisation tools such as Tableau, Power BI, or visualisation libraries in Python (matplotlib, Seaborn).
                                                                         • • Experience with big data technologies such as Hadoop, Spark, or distributed computing frameworks.
                                                                           • • Strong understanding of data preprocessing, feature engineering, and data pipeline development.

                                                                             • Preferred Skills:

                                                                               • Experience with cloud platforms like AWS, Google Cloud, or Azure for building data science models in the cloud.
                                                                               • • Knowledge of NLP (Natural Language Processing), computer vision, or time series analysis.
                                                                                 • • Familiarity with NoSQL databases (e.g., MongoDB, Cassandra).
                                                                                   • • Experience with CICD pipelines for model deployment and monitoring.
                                                                                     • • Handson experience with AB testing, randomised experiments, and designing controlled experiments.
                                                                                       • • Familiarity with tools like Docker and Kubernetes for containerising models and applications.

                                                                                         • Personal Attributes:

                                                                                           • Strong analytical and problemsolving skills with a passion for datadriven decisionmaking.
                                                                                           • • Ability to work independently, prioritise tasks, and manage multiple projects at once.
                                                                                             • • Excellent communication skills, capable of explaining complex concepts to both technical and nontechnical audiences.
                                                                                               • • A collaborative mindset, with a willingness to work with crossfunctional teams to achieve business objectives.
                                                                                                 • • Curious and continuously eager to learn new techniques, tools, and technologies in the data science space.

                                                                                                   • Given that this is just a short snapshot of the role we encourage you to apply even if you dont meet all the requirements listed above. We are looking for individuals who strive to make an impact and are eager to learn. If this sounds like you and you feel you have the skills and experience required, then please apply now.

                                                                                                     Benefits

                                                                                                     About your team

                                                                                                     Join our growing Data & Analytics practice and make a difference.

                                                                                                     In this practice you will be utilizing the most innovative technological solutions in modern data ecosystem. In this role you’ll be able to see your own ideas transform into breakthrough results in the areas of Data & Analytics strategy, Management & Governance, Data Integration & engineering, Analytics & Data science.

                                                                                                     About Infosys Consulting

                                                                                                     Be part of a globally renowned management consulting firm on the frontline of industry disruption and at the cutting edge of technology. We work with market leading brands across sectors. Our culture is inclusive and entrepreneurial. Being a midsize consultancy within the scale of Infosys gives us the global reach to partner with our clients throughout their transformation journey.

                                                                                                     Our core values, ICLIFE, form a common code that helps us move forward. ICLIFE stands for Inclusion, Equity and Diversity, Client, Leadership, Integrity, Fairness, and Excellence. To learn more about Infosys Consulting and our values, please visit our careers page.

                                                                                                     Within Europe, we are recognized as one of the UK’s top firms by the Financial Times and Forbes due to our client innovations, our cultural diversity and dedicated training and career paths. Infosys is on the Germany’s top employers list for 2023. Management Consulting Magazine named us on their list of Best Firms to Work for. Furthermore, Infosys has been recognized by the Top Employers Institute, a global certification company, for its exceptional standards in employee conditions across Europe for five years in a row.

                                                                                                     We offer industryleading compensation and benefits, along with top training and development opportunities so that you can grow your career and achieve your personal ambitions. Curious to learn more? We’d love to hear from you.... Apply today!