Lead/Senior Data Scientist

DVT is a global custom software development and data engineering company. With our remote and hybrid options, our vision is to be South Africa's favourite custom software solutions & services company, with a global footprint. You will have the opportunity to work alongside some of the most established developers in the country with the latest technologies. DVT is committed to continuously training our staff and we are very proud of our culture of learning, from internal speaking and training to sponsoring a variety of technical events from DevConf to GDG.

DVT is looking for a Lead Data Scientist to assist on a complex and intricate project in the renewable energy sector.

Education & Experience:

8-10 years of experience working on Data Science projects and ideally having led some of them.
Knowledge of the usual tools such SQL, Sci-Kit lean, Pandas, Numpy, Jupyter notebooks.
Exceptional knowledge of Machine Learning techniques on both the supervised and unsupervised learning fronts.
Exceptional knowledge of time series forecasting.
Track record and demonstratable knowledge of using the above algorithms to solve problems at client or at their employer.
Fairly well versed and good understanding on MLOps best practices and has been a part of a team that has taken models to prod, ideally at scale.
Knowledgeable of MLOps tools like MLFlow, DVC, Airflow or cloud MLOps environments like Sagemaker, Azure ML studio of GCPs vertex AI. Nice to have if they have practical experience.
Databricks experience is a nice to have.

Strong knowledge and extensive experience in:

Programming Languages such as Python, R, Scala, and SQL.
Data Processing and Analysis tools such as NumPy, SciPy, and Pandas.
Big Data technologies such as Hadoop, Spark, and Hive
ML frameworks and Libraries such as: Scikit-learn, TensorFlow, Keras, PyTorch
Experiment Management Tools such as: MLFlow, DVC, and TensorBoard
Data Visualization tools such as Tableau, PowerBI, Matplotlib, and Seaborn
Cloud technologies such as AWS, Azure, GCP, or Databricks

Strong knowledge and understanding of:

Various Supervised Learning Algorithm such Regression, Decision Trees, Random Forests, Support Vector Machines, K-Nearest Neighbours
Various Unsupervised Learning Algorithms: K-Means, Principal Component Analysis

Roles and Responsibilities:

Work independently on complex projects.
Design and implement complex predictive models or algorithms to drive business growth and improve customer experiences
Identify patterns and trends in data to drive insights and recommendations for business decisions
Design experiments and A/B testing to validate hypotheses and assess impact of data-driven solutions
Mentor and provide guidance to junior and intermediate data scientists.
Be involved in project management and strategic decision-making
Be involved in data pipeline architecture design and implementation Collaborate with cross-functional teams to gather requirements, design solutions, and implement models
Communicate findings and recommendations to non-technical stakeholders in a clear and concise manner

Behaviour Competency:

Self-motivated, proactive and results-oriented
Strong analytical and problem-solving skills
Ability to work in a fast-paced, dynamic and collaborative environment
Comfortable with ambiguity and able to adapt to change
Ability to work independently and as part of a team
Passion for learning new technologies and staying up to date with the latest trends in data science and machine learning
Excellent written and verbal communication and collaboration skills
Shows promising leadership abilities
Strong business acumen

Interview Process