About the job
Responsibilities:
machine learning models solving business problems at a scale in an accurate fashion.
data required to feed machine learning models.
large, complex data sets from client and external sources that meet functional business requirements.
models into production and follow-up with performances and take corrective actions if required.
machine learning outcome and clearly convey the added value to the business.
analytics tools to provide actionable insights into customer acquisition, operational efficiency, and other key business performance metrics.
complex problems into smaller pieces and plan accordingly to accurately make project timeline estimates.
know-how: Our Data Scientists have a broad knowledge of a variety of data and mathematical solutions.
with management to get stakeholder feedback, get alignment on approaches, deliverables, and roadmaps
data cleaning/hygiene, data QC, and integrate data from both client internal and external data sources on Advanced Data Science Platform.
statistical data analysis, including exploratory data analysis, data mining, and document key insights and findings toward decision making
validate, and cross-validate predictive models and machine learning algorithms using state of the art Data Science techniques and tools
predictive models/machine learning results that can be incorporated into client-deliverable documentation
Assist client to deploy models and algorithms within their own architecture
Qualifications :
degree in Computer science, Engineering, Applied Mathematics or a related quantitative field
years Professional experience in Advanced Data Science, such as predictive modeling, statistical analysis, machine learning including time series forecasting, regression and classification, and video recognition
with one or more Advanced Data Science software languages (Python, SQL, Spark)
experience in Cloud technologies (AWS, Azure, GCP), preferably with Databricks and data lakes
Experience with SQL and relational databases, query authoring and tuning as well as working familiarity with a variety of databases topologies
Requirement:
have hands-on experience in customer centric solutions production solutions analyzing customer behavior and /or physiological metrics.
have hands-on experience in building ML production systems making recommendation to end-users.
have video processing / facial recognition experience.
ability to deploy machine learning models from the research environment to production via procedural or pipeline approaches.
problem-solving skills; ability to pivot complex data to answer business questions.
Good communication and presentation skills.
Nice to have hands-on LLM and prompt engineering experience
to have recommendation engine / Chatbots / Fraud detection
to have experience in causal inference
to have ability to visualize data for influencing (Qlik, PowerBI, Tableau)
Good appreciation for the Agile/Scrum methodology
Ability to prove statistical significance of any business decision / sampling and other
Seniority Level: Other
Job Functions: Data Science & Analytics
Industries : Information Technology
