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Incelligent

Data Scientist/ AI Developer

Posted 8 Days Ago
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In-Office
Nea Smyrni
Mid level
In-Office
Nea Smyrni
Mid level
The role involves designing predictive ML algorithms, integrating models into production, analyzing datasets, and presenting findings. Requires expertise in ML techniques and strong programming skills.
The summary above was generated by AI

We are looking for a bright Machine Learning Engineer to join our growing engineering team in Athens.

Who We Are

Incelligent provides software solutions to help large corporations achieve digital transformation through the usage of Big Data and ML-powered Analytics. Our platform enables industrial deployment of AI models as part of integrated predictive analytics solutions for various domains such as Banking/Financial Institutions (Risk, Marketing), Retail (Recommendation), Telecommunications (Forecasting, KPI modelling), Compliance (Image Processing). We also perform research and development activities that involve state-of-the-art ML techniques (e.g. LSTM, CNN, GAN, ODENet, GNN) for our product roadmap.

What You Will Be Doing

  • Design and develop new predictive machine learning and artificial intelligence algorithms for multiple industrial domains
  • Integrate ML models into the production pipeline of our solutions
  • Analyze datasets to identify patterns and extract insights
  • Visualize and present dataset findings and features

Requirements

Minimum requirements:

  • MSc in Artificial Intelligence, Data Science, Statistics or other related fields
  • Minimum 3 years of experience in data science/ML using at least one of Python, Scala & Java
  • Strong SQL knowledge is required for data probing/preparation
  • Verified knowledge of descriptive statistics, correlation analysis and hypotheses testing
  • Experience in applied traditional/shallow learning techniques for supervised and unsupervised tasks (scikit-learn, other)
  • Verified model tuning experience including model performance analysis, error KPIs and hyperparameter tuning via cross validation techniques
  • Experience at least one python deep learning framework for neural networks: TensorFlow, Keras, PyTorch
  • Industrial or academic experience with at least one deep-learning model family (RNN, CNN, GAN, DRL, DBN, etc.)
  • Knowledge of code version control via Git

Nice to have:

  • PhD in Artificial Intelligence, Data Science, Deep learning or related fields.
  • Experience with ML-Ops framework adaptation (e.g. ML-Flow-Tracking, PyCaret)
  • Knowledge of data science and data visualization tools (Jupyter, Superset, Zeppelin or other)
  • Experience with Big Data - infrastructure & query engines (Spark, HDFS, Hive, Impala, Trino) as well as Big ML tools (e.g. SparkML)
  • Familiarity in deploying ML models as REST APIs (MLFlow Serve, PyCaret, FastAPI)
  • Familiarity with Docker and application packaging

Other qualifications

  • Strong oral and written communication skills
  • Fluent in English
  • Native/ fluent Greek, oral and written
  • Eagerness to learn modern technologies
  • Ability to deliver in time-critical situations in an organized way
  • Analytical capabilities and attitude to problem solving
  • Team motivation

Benefits
  • Highly competitive salary based on your skills, reviewed upwards on a regular basis, based on your performance.
  • Participation in state-of-the-art projects and tech challenges
  • Personal and professional development, amongst industry experts and talented people
  • Continuous learning, having access to broad resources for professional and personal development
  • Friendly environment and fun team member

Commitment to Equal Employment Opportunity: All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, pregnancy, disability, age, or other characteristics. We respect your personal data.
All personal information in your application and CV will remain strictly confidential.

Top Skills

Docker
Fastapi
Git
Hdfs
Hive
Impala
Java
Keras
Mlflow
Pycaret
Python
PyTorch
Scala
Scikit-Learn
Spark
SQL
TensorFlow
Trino

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