Urgent requirement | DATA SCIENTIST , NEW YORK (C2C)

 
 
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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)



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