We are excited to welcome a talented and experienced Data Scientist to our team. As a Data Scientist, you will have the opportunity to work on a variety of projects and industries while working with a team of experienced professionals. You will be able to access cutting-edge tools and technologies and have ongoing learning and development opportunities to help you grow your skills. We are looking for someone who is passionate about data science and is committed to staying up to date with the latest advancements in the field. If you meet our mandatory qualifications and possess some or all our preferred qualifications, we encourage you to apply and join our team.
Job Summary
As a Data Scientist, you will be responsible for working with large amounts of data to develop insights and solutions for various industries. You will be working closely with cross-functional teams to identify business problems and develop solutions using AI/ML algorithms. The ideal candidate will have an associate-level cloud certification and experience with developing and deploying ML models to production environments. Additionally, the candidate should have experience in data visualization, big data technologies, deep learning frameworks, problem-solving skills, and agile development methodologies.
Key Responsibilities:
Analyse large data sets to identify patterns and insights and develop predictive models using machine learning algorithms.
Provide AI and ML consulting to clients, including estimating development timelines and providing solutions using AWS, Azure, GCP, Data Bricks, and other tools.
Work on multiple projects simultaneously, effectively managing timelines and resources to ensure successful project delivery.
Build custom NLP models for various use cases, such as multi class text classification, topic identification and text-based emotion recognition.
Mentor junior team members, providing guidance and support as needed to help them grow and develop their skills.
Translate technical jargon into understandable language for stakeholders and clients, effectively communicating the value of technical solutions.
Present findings and solutions to stakeholders and clients, providing recommendations for how to use the data to drive business value.
Continuously research and learn new techniques and technologies to stay up to date with the latest advancements in AI/ML.
Mandatory Qualifications
Bachelors or masters degree in computer science, Statistics, Mathematics, or a related field.
At least 3 years of experience in data analysis, data mining, machine learning and Deep learning.
Strong experience with programming languages such as Python and SQL.
Strong understanding of statistical methods and data analysis techniques.
Experience with AI/ML frameworks such as TensorFlow, Keras, and PyTorch.
Experience with cloud computing platforms such as AWS, Azure, and GCP.
Strong understanding of NLP and time series analysis. Has academic knowledge of image processing and CV.
Excellent communication and presentation skills, with the ability to effectively communicate complex technical solutions to stakeholders and clients. Proven ability to work independently and as part of a team and to work on multiple projects simultaneously, effectively managing timelines and resources to ensure successful project delivery.
Familiarity with agile development methodologies, testing, and code reviews and version control tools such as Git.
Passion for continuous learning and professional growth in the field of data science.
Preferred Qualifications:
Associate-level cloud certification (such as AWS Certified Developer Associate or Microsoft Certified Azure Administrator) is preferred.
Experience in developing and deploying ML models to production environments. Working with containerization technologies such as Docker and Kubernetes.
Understanding of data visualization techniques and tools such as Tableau, Power BI, or D3.js.
Experience working with AutoML libraries such as EvalML, H2O.ai, TPOT, or Auto-sklearn.
Proficiency in multiprocessing, as well as experience with distributed computing frameworks such as PySpark.
Knowledge of big data technologies such as Hadoop, Spark, or Kafka.
Strong problem-solving skills and the ability to think creatively to develop innovative solutions.
Experience with data warehousing and ETL tools such as AWS Glue, DataBricks, Google BigQuery.
Knowledge of graph theory, social media network analytics, graph networks, and experience with graph databases such as Neo4j.
Competitive salary and benefits package.
Opportunity to work on a variety of projects and industries.
Opportunity to work with a team of experienced and talented professionals.
Access to cutting-edge tools and technologies.
Opportunity to grow and develop your skills through ongoing learning and development opportunities.