• Solve complex business problems with data and use data scientific tools to find solutions for challenges in the realm of both big & small data
• Actively participate in cross-functional project teams in the execution of data and analytics strategy
• Mine and analyze data from company databases to drive optimization and improvement of product development, marketing techniques, and business strategies
• Develop custom data models and algorithms to apply to data sets
• Develop processes and tools to monitor and analyze model performance and data accuracy
• Partnering with others across the business to build prototypes and new approaches for capturing data and analyzing employee behavior.
• Designing experiments to confirm assumptions and answer questions.
• Consulting with cross-functional partners and senior leaders on insights, trends, and data-driven recommendations and solutions.
• Finding ways to simplify activities by creating libraries, utilities and code.
• Partner with IT to effectively migrate analytical models from prototype to production.
• Build analytics products so users have access to insight at their fingertips.
• Learn new techniques and get the “full-stack analytics” skillset, from front-end to backend development and everything in between.

Skills: Data Analysis, Data Modeling, Cross-Functional Collaboration, Algorithm Development, Experiment Design, Model Monitoring, Insight Generation, Product Development

• Analyze current technical challenges and plan research and development projects to develop products for the markets of the future.
• Define data architectures, organizational structures and processes.
• Determine the manpower required for the products.
• Put together the tech stack and the teams.
• Represent the solutions to customers and manage various stakeholders.
• Finding creative solutions for real-world problems. 
• Keep digging until the entire problem has been mapped and solved.
• Performing data cleansing, data wrangling, and statistical analysis of time series data provided by OMP’s customers.
• Visualizing findings and presenting them to customers in a way that a non-technical audience can understand.
• Keeping an overview at all times, coordinating and collaborating with functional experts, advisors, software engineers, and the customer.
• Providing support to users and internal data science and consulting teams.
• Improving the OMP planning solution through research and development.

Skills: Technical Analysis, Data Architecture, Resource Planning, Tech Stack Development, Stakeholder Management, Creative Problem Solving, Data Visualization, Collaboration

• Evangelising DSpark's products and services to clients
• Analysing technical and business requirements for clients using DSpark's Product Management Framework
• Building Proofs-of-Concept (POCs), including data extraction, analysis, visualisation and reporting to demonstrate value for clients
• Provide technical input to client proposals, including product selection, feasibility and effort.
• Interpreting and transforming data into usable and impactful outputs for clients
• Lead client engagements from pre-sales through to final delivery in coordination with the Director of Data Science and the sales team
• Assist with writing proposals and tenders from a technical perspective
• Mentor and guide junior team members, including peer-reviewing code outputs/deliverables
• Liaise with clients and technical team to translate business requirements into data
• driven solutions.
• Collaborate with senior stakeholders to put business value at the core of project delivery
• interpreting technical data concepts to business context.
• Create and own project/product visions to enable project teams to deliver outstanding
• business value.
• Understand the key technology trends in Analytics &amp, AI domain and their business impact.
• Interact, collaborate, and share experiences with colleagues from different disciplines and backgrounds.

Skills: Product Evangelism, Requirements Analysis, Proof of Concept, Technical Proposal Development, Data Transformation, Client Engagement, Mentoring, Stakeholder Collaboration

• Review raw requirements to understand key outcomes expected by clients
• Identify, join, explore data from multiple disparate sources and formats 
• Reduce large quantities of unstructured or formless data into a form which can be analyzed
• Collaborate with clients’ IT teams to develop, implement and evolve data gathering processes
• Clean, enhance, profile, and mine structured and unstructured data
• Understand portfolios, user behaviors, and long-term trends
• Devise quantitative research strategies to inform project outcomes
• Implement statistical and computational algorithms to analyze client data and provide insights into how people borrow and save, use financial products, interact with financial institutions, etc.
• Prototype and deploy machine learning algorithms 
• Support and expand on existing tools and modules currently in use at BFA
• Integrate analysis with qualitative and quantitative output from others

Skills: Requirements Review, Data Integration, Data Transformation, Process Development, Data Cleaning, Behavior Analysis, Quantitative Research, Machine Learning Prototyping

• Guide BFA colleagues in other teams on data-related tasks
• Proactively incorporate cutting-edge theoretical and practical methodologies while implementing data analytics algorithms
• Create and disseminate knowledge articles (blog posts, focus notes, case studies, white papers, best practice documents, etc.) through appropriate channels 
• Keep up with the upcoming trends in data analytics and constantly strive to learn and improve on the same
• Interact with the client on a regular basis to provide regular project status update, and resolve any issues
• Coordinate with other BFA team members to produce high quality deliverables 
• Present analysis to the client along with senior stakeholders in the organization
• Coordinate knowledge dissemination within the company through “BFA University,” brown bags, and BFA’s Slack Community
• Support recruitment efforts by conducting technical face-to-face interviews
• Train current and new team members on data analytics processes to increase throughput and improve redundancy

Skills: Team Guidance, Data Methodology Implementation, Knowledge Creation, Trend Awareness, Client Interaction, Quality Coordination, Analysis Presentation, Training and Recruitment

• Perform qualitative and quantitative analyses to identify patterns, trends and issues relevant to communication, knowledge and innovation activities, and to inform the development of future efforts.
• Use web-based data collection tools to gather and analyze information about public digital conversations and digital audiences on an ongoing and systematic basis
• Maintain, audit and governance the digital intelligence data collection on IDB brands and sectors.
• Support research projects that leverage public opinion data (online news and social media) to understand a given topic, sector or country to inform strategies and provide inputs for business performance analyses.
• Develop data visualization dashboards to provide stakeholders with tools for decision-making and to socialize digital data across the IDB.
• Identify gaps in the data collection process and integrate new datasets, technology and techniques into ISU’s analytics processes.
• Develop new analytical (network and predictive) models to better inform decision-making and identify influencers.
• Provide technical guidance to specialists within and outside KIC regarding data strategy, data collection and processing, report and insight generation.

Skills: Qualitative Analysis, Data Collection, Data Governance, Public Opinion Research, Data Visualization, Process Improvement, Predictive Modeling, Technical Guidance

• Strong interest in applying data science to solve real-world business problems
• Highly self-motivated to deliver both independently and with strong team collaboration.
• Desire to creatively take on new challenges and work outside comfort zone.
• Strong written and oral communications along with presentation and interpersonal skills.
• Strong aptitude & desire for learning new technologies and analytics techniques.
• Good written and verbal communication skills for teaching and reporting
• Good listener, pay attention to other people’s points of view
• Strong team spirit and enjoys working in teams composed of people from different fields and backgrounds
• Independent and enjoy going the extra mile
• Greek and English fluency as lectures could take place in either language

Qualifications: BA in Economics with 2 years of Experience

• Proficiency in Python is required along with hands-on experience with Client/DL libraries like Numpy, Pandas, scikit-learn, TensorFlow, pytorch, Mathplotlib, etc
• Good knowledge of statistics and probability distributions
• Experience in handling image data using python libraries like OpenCV, sci-kit-image etc
• Deep understanding of common Machine Learning techniques related to Time series, Regression, Classification, Clustering, etc.(e.g. KNN, SVM, Random Forest, GBM, XGBoost, ARIMA, etc) and their applications Proficiency with at least one deep learning framework such as PyTorch, TensorFlow, Keras, etc.
• Experience in Optical Character Recognition and Document Digitization problems preferred
• Working knowledge in deep learning with different NN architectures like CNN, RNN, LSTM, GANs Auto encoders, Transformers, YoLo etc.
• Should be able to adapt available models from open source domain and implement research papers based on use-case requirements
• Working experience in end to end data science project life cycles from use case framing, data collection, data exploration, model building, deployment
• Understanding of big data related technologies and DevOps (Dockers, Singularity) Other skills/ expectations
• Good communication and presentation skills
• Proven ability to be creative and analytical in troubleshooting issues

Qualifications: BS in Data Science with 4 years of Experience

• Strong background in time series, business forecasting, and demand modelling
• Experience predicting monthly unit sales quantities and inventory demand
• Exceptional coding skill in either R or Python
• Familiar with using cloud technologies for distributed computing 
• Great communicator, collaborator, and influencer, and love working with business stakeholders
• Experience developing scalable machine learning models
• Familiar developing data pipelines for large scale implementation
• Knowledge of Agile systems and tools
• Fluency in Big Data Programming (Spark, PySpark, SparkR, etc)
• Experience with Supply Chain forecast modelling
• Experience with Seasonality Adjustments and Causal Analysis
• Hands on experience developing end-to-end machine learning pipelines

Qualifications: BS in Computer Science with 5 years of Experience

• Practical experience from industry and professional services in delivering significant and valuable advanced analytics projects and/or assets
• Engagement of technical and senior stakeholders
• Ability to manage and coach a team of data scientists
• Delivery of projects on time and within budget for high profile clients
• Understanding of requirements for software engineering and data governance in data science
• Experience in Data Science/ Data Analyst/ Data modeling or similar role
• Experience in Python/ R/ SQL
• Proficient with Microsoft Office
• Strong communication skills, excellent in both written and spoken English
• Open-minded with good business sense

Qualifications: BS in Statistics with 3 years of Experience

• Data science experience deploying models in a professional
• Experience with visualization libraries and tools like matplotlib, d3.js, Tableau, Power BI
• Ability to build machine learning models from the ground up (Python/R)
• Experience with time series and NLP
• Subject matter expert who can provide advice around supply chain optimization and analytics
• Experience with optimization software to apply integer programming, mixed-integer programming, non-linear programming, and stochastic optimization
• Deep learning models for drive failure predictions and driver recommendations
• Knowledge of advanced statistical techniques and concepts (regression, classification, hypothesis testing, Bayesian analysis, etc.)
• Experience in big data technologies (Hadoop, Spark, MAP\Reduce, Hive, IMPALA among others)

Qualifications: BS in Mathematics with 8 years of Experience

• Experience with managing diverse data sources, including preprocessing, cleansing, and verifying the integrity of data to develop data marts for data science use cases and machine learning applications
• Experience with performing data exploration and data analysis in support of analytics objectives
• Ability to thrive while working independently to achieve successful results with minimal guidance
• Ability to exhibit flexibility and initiative when dealing with ambiguous and fast-paced situations
• Ability to obtain a security clearance
• Technically strong when handling data
• Experience with Data Visualisation, Power BI
• Understand of development process
• Understanding of version control
• Experience in web scraping

Qualifications: BS in Information Technology with 3 years of Experience