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Role: Data Scientist - Consultant
Location: New York, US
JD:
∙ In this role, you would be responsible to drive data-derived insights by developing advanced statistical models, machine learning algorithms and computational algorithms based on business initiatives
∙ Direct the gathering of data, assessing data validity and synthesizing data into large analytics datasets to support project goals
∙ Utilize big data analytics and advanced data science techniques to identify trends, patterns, and discrepancies in data. Determine additional data needed to support insights.
∙ Build and train statistical models and machine learning algorithms for replication for future projects
∙ Communicate recommendations to business partners and influencing future based on insights
∙ Play a hands-on, advisory and partner role to help solving the business problems.
Responsibilities!
∙ Play a key role to solve complex problems, pivotal to business and drive meaningful insights from petabytes of data
∙ Utilize product approach to build, scale and deploy holistic data science products after successful prototyping
∙ Demonstrate incremental solution approach with agile and flexible ability to overcome practical problems
∙ Lead an analytic solution module, or work as part of larger team in data science projects
∙ Partner with senior team members to assess customer needs and define business questions
∙ Clearly articulate and present recommendations to business partners, and influence future plans based on insights
∙ Work with customer centric approach to deliver high quality business driven analytic solution
∙ Drive innovation in approach, method, practices, process, outcome, delivery, or any component of end-to-end problem solving
∙ Promote and support company policies, procedures, mission, values, and standards of ethics and integrity
∙ Demonstrates up-to-date expertise and applies this to the development, execution, and improvement of action plans
∙ Develop analytical models to drive analytics insights
∙ Participate in large data analytics project teams
∙ Model compliance with company policies and procedures and supports company mission, values, and standards of ethics and integrity
∙ Participate in the continuous improvement of data science and analytics, Present data insights and recommendations to key partners and provide and support the implementation of business solutions
∙ Present information using data visualization techniques.
∙ Communicate results and ideas to key stakeholders / decision makers.
∙ Help building a research environment and deploy models to production in a more standard python-based stack
Qualifications/ Minimum qualifications
∙ University Degree (Any Field)
∙ Strong experience with Python + ML
∙ 10+ years' practical experience as a Data Scientist with proven track record
∙ Experience building a research environment and deploy models to production in a more standard python-based stack
∙ Project experience – Hands-on experience on taking an enterprise project/application from inception to production.
∙ Experience in playing hands-on, advisory and partner role to help solving the business problems.
Preferred qualifications
∙ Experience with statistical programming languages (for example, SAS, R, +AI).
∙ Experience with SQL and relational databases (for example, DB2, Oracle, SQL Server).
∙ High proficiency in data mining, modeling, validation and insight generation.
∙ Excellent working knowledge of statistics, mathematics and machine learning algorithms.
∙ High proficiency in coding languages, including Python and SQL.
∙ Ability to work with large data sets. Has sound understanding of big data technology stack
∙ Understanding of cloud computing platforms and large-scale databases
∙ Demonstrable ability to collaborate and work in teams
∙ Excellent with communications and partner engagement
∙ Experience with B2B, Financial Industry, Asset Management, Financial Market Data, Sales & Marketing is helpful.
∙ Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks.
∙ Knowledge of sophisticated statistical techniques and concepts (regression, properties of distributions, statistical tests and accurate usage, etc.) and experience with applications.
∙ Knowledge and experience in statistical and data mining techniques: GLM/ Regression, Random Forest, Boosting, Trees, text mining, social network analysis, etc.
∙ Expertise querying Relational / No-SQL databases and using statistical programming languages like R, Python, etc.
∙ Experience with distributed data/computing tools: Hadoop, Hive, Spark, etc.
∙ Experience visualizing/presenting data for partners using: Business Objects, Tableau, D3.js, ggplot, etc.
∙ Experience with data-science tools: Dataiku, Jupyter, etc.
∙ Knowledge of opensource, 3rd party, cloud based data science / NLP / machine learning platforms (e.g. AWS or Azure offerings)
If you are interested , Please fill below your details :
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Reason for change/Interest*
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