Recruise India Consulting Pvt Ltd
Location
Chennai | India
Job description
Responsibilities :
Analyze complex and large datasets from various sources, including market, product, customer, sales, and marketing data, to identify patterns, trends, and correlations that provide actionable insights for improving business outcomes.
Develop and deploy predictive models using advanced statistical and machine learning techniques to support enhanced business understanding of sales trends, segmentation, customer behaviors, and performance, enabling proactive decision-making and strategic planning.
Create visually appealing and informative data visualizations to effectively communicate key insights, trends, and performance metrics to stakeholders at various levels of the organization.
Ensure data integrity, accuracy, and consistency by implementing data quality standards, data governance policies, and best practices to maintain high data quality across relevant systems and databases.
Collaborate closely with cross-functional teams, including business leaders, analysts, and IT teams, to understand business needs, align strategies, and translate business questions into data-informed solutions.
Effectively communicate complex technical concepts, insights, and recommendations to both technical and non-technical stakeholders through presentations, reports, and clear documentation.
Stay updated on industry trends, emerging technologies, and best practices in data science, business analytics and the asset management industry to identify new opportunities, tools, and methodologies that drive continuous improvement and innovation.
Qualifications:
Master's/bachelor's degree from Premier institute in data science, Statistics, Computer Science, Mathematics, Economics, or a related field.
2 -8 years of experience working as a Data Scientist or in a similar analytical role, with a focus on driving business outcomes through data analysis and insights. Experience in financial services, asset management industry is a plus.
Strong analytical skills and proven ability to analyze complex datasets, derive actionable insights, and translate them into tangible business outcomes and recommendations.
Proficient in programming languages such as Python and R, and experience with data manipulation, analysis, and visualization libraries (e.g., pandas, NumPy, Matplotlib, seaborn).
Solid understanding of machine learning algorithms, model evaluation, and feature engineering. Experience with frameworks like scikit-learn or TensorFlow is desirable. Interest and/or experience using new machine learning platforms, such as H2O, is a plus.
Proficiency in statistical modeling techniques such as regression, clustering, time series analysis, and hypothesis testing.
Ability to understand business objectives, market dynamics, and customer behavior to effectively contribute to Distribution business outcomes.
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