LEAD DATA SCIENTIST SKILLS, EXPERIENCE, AND JOB REQUIREMENTS

Updated: Jan 10, 2026 - The Lead Data Scientist has experience guiding Data Science teams and implementing Machine Learning algorithms like regression and classification. This role requires proficiency in big data technologies such as Spark and SQL, and is skilled in deploying machine learning models in cloud environments like Azure and AWS. The lead also communicates complex data science concepts effectively and utilizes data visualization tools like Tableau while employing Agile methodologies.

Essential Hard and Soft Skills for a Standout Lead Data Scientist Resume
  • Data Modeling
  • Machine Learning
  • Statistical Analysis
  • Data Visualization
  • Programming
  • Big Data Technologies
  • Data Mining
  • SQL and NoSQL Databases
  • Predictive Analytics
  • Natural Language Processing
  • Leadership
  • Communication
  • Problem-Solving
  • Critical Thinking
  • Collaboration
  • Adaptability
  • Creativity
  • Time Management
  • Attention to Detail
  • Mentoring and Coaching

Summary of Lead Data Scientist Knowledge and Qualifications on Resume

1. BS in Data Science with 7 years of Experience

  • Experience with building predictive models
  • Experience in developing predictive models around fraud, risk, insider threat or other rare events
  • Experience in running efficient queries on large relational databases, including Oracle or SQL Server
  • Experience with data science, machine learning, or modeling
  • Experience with the full lifecycle of machine learning development and deployment including gathering requirements, identifying data, preparing data, and building, validating and deploying predictive models
  • Experience in providing technical direction and leadership to data science teams, including the best way to handle analytic ad hoc requests
  • Experience in R, Python, or PySpark
  • Experience working with and presenting to nontechnical clients who have minimal expertise in AI or ML
  • Ability to create effective solutions and strategies for clients that might be lacking data or technology
  • Knowledge of the landscape of technology capabilities around AI and ML

2. BS in Computer Science with 10 years of Experience

  • Hands-on experience with ML, coding in Python/PySpark, distributed computing
  • Have an inquisitive mind, research and generate ideas, be comfortable with large-scale data
  • Understand the modern machine learning landscape and its mathematical foundations
  • Common sense, business-driven, results-oriented, agile mentality, do-it and own-it culture
  • Strong communication (written, spoken), presentation skills, eye level with business and PO
  • Experience in people and project management (leading), business-relevant skills
  • Experience in the deployment of machine learning solutions and full-stack development
  • Experience with cloud AI environments, including Databricks, Azure ML or AWS Sagemaker
  • Experience in working with financial transactions or payments
  • Knowledge of Agile and Scrum processes
  • Self-starter, independently initiating and driving projects toward completion.

3. BS in Statistics with 9 years of Experience

  • Experience translating data to insight into recommendations
  • Expertise in machine learning and statistical analysis approaches such as classification, clustering, regression, statistical inference, collaborative filtering, etc.
  • Experience managing advanced analytics projects that solve complex analytical problems using data mining technologies
  • Expertise in automating and deploying models in production systems
  • Experience with Big Data technologies (AWS EMR, Spark, Presto, Hadoop, etc.)
  • A true passion for understanding customer behavior on-platform and in-game
  • Expert analytical and problem-solving skills, plus the ability to innovate and work independently
  • Strong skills in statistical methods (e.g. hypothesis testing, time series modeling)
  • Strong SQL skills and strong Python or R skills, familiarity with Jupyter or RStudio
  • Familiar with Hadoop, Apache Spark framework, SQL/NoSQL, Snowflake
  • Strong skills in building dashboards and visualizations (e.g Tableau, PowerBI, Quicksight)

4. BS in Mathematics with 6 years of Experience

  • Hands-on data science experience
  • Previous experience managing a Data Science team
  • Deep experience with Python, R, Julia or other statistical programming languages
  • Familiarity with Git source control management
  • Proven ability to develop solutions to loosely defined business problems by leveraging pattern detection over large datasets 
  • Proficiency in statistical analysis, quantitative analytics, forecasting/predictive analytics, multivariate testing, and optimization algorithms 
  • Experience working on agile/scrum teams
  • Ability to work independently with little supervision
  • Strong communication and interpersonal skills, including translating technical work for non-technical audiences
  • A burning desire to work in a challenging fast-paced environment

5. BS in Information Technology with 5 years of Experience

  • Experience working with health care datasets including medical and pharmacy claims, and EMR/EHR.
  • Experience building healthcare algorithms, models, or metrics
  • Experience working with SQL or Python
  • Experience with R or SAS
  • Experience in working with and wrangling data from AWS S3 buckets
  • Experience working with Redshift 
  • Experience with additional AWS Services such as Amazon EMR and AWS Lambda
  • Experience with managing code repositories (using Github or Bitbucket)
  • Excellent communication and documentation skills
  • Ability to thrive within a cross-functional collaborative environment with analysts, developers, and product management

6. BS in Software Engineering with 7 years of Experience

  • Experience in leading and growing teams of Data Scientists
  • Experience in implementing Machine Learning algorithms (e.g. regression, classification, topic modeling, time series).
  • Experience in Python, Scala/Java
  • Experience working with big data technologies (Spark, Hadoop, Hive, Redshift, SQL or similar)
  • Experience with Data science toolkits for ML and deep learning (sci-kit-learn, SparkML, Tensorflow, Keras)
  • Experience in Agile development methods
  • Experience working in cloud environments (Azure, GCP, AWS, etc)
  • Experience with data visualization tools (Tableau, QlikView, etc)
  • The ability to deploy machine learning models and systems to production
  • Able to articulate complex data science concepts to both technical and non-technical audiences

7. BS in Artificial Intelligence with 5 years of Experience

  • Working experience in Data manipulation and statistical modeling as a Scientist, Consultant, Architect, DBA, or Engineer
  • Working experience in SQL/R/SAS Programming
  • Experience in the telecommunications industry, or two other consumer-based industries
  • Experience with Teradata such as SQL, UDFs, interpreting explain plans, basic performance-tuning, and use of the database catalog
  • Background with Cable systems and operations
  • Experience with Hadoop, particularly HIVE and Spark
  • Knowledge of other relevant tools such as SAS, SPSS, Alteryx, and Linux
  • Knowledge of other relevant techniques such as text analysis and text mining
  • Familiarity with the open-source ecosystems surrounding R (CRAN), Python (PyPi), and/or Hadoop

8. BS in Machine Learning with 6 years of Experience

  • Experience in statistical data analysis, model evaluation, ETL, and building machine learning models or research experience in the academic setting
  • Experience with big data, using Spark, Hadoop and Hive
  • Expertise in using R, Python, and PySpark to manipulate large data sets and develop statistical models
  • Experience with Cloud technologies like AWS/GCP/Azure
  • Experience in the end-to-end lifecycle of model development
  • Excellent problem-solving skills, critical thinking and conceptual thinking abilities
  • Solid understanding of the health care industry, products, and systems
  • Experience in statistical data analysis, model evaluation, ETL, or research experience in an academic setting
  • Previous experience leading projects or leading a team of project-related goals
  • Able to communicate technical ideas and results to non-technical clients in written and verbal form

9. BS in Data Science with 7 years of Experience

  • Progressive experience in developing and designing technology solutions
  • Practical data science experience in the application of statistics, machine learning, and analytic approaches
  • Proven track record of solving critical business problems and uncovering new business opportunities
  • Extensive experience designing and training models, integrating data from disparate systems, and cleaning data
  • Solid experience of data visualization tools such as Pyqtgraph and/or Power BI and/or Tableau, etc.
  • Hands-on experience with prototyping/proof-of-concept development and stakeholder management
  • Hands-on experience of Python and/or R, associated tools (TensorFlow, pandas, scikit-learn, numpy) and IDEs (PyCharm, Eclipse, RStudio)
  • Ability to write complex queries that are accessible, secure, and perform in an optimized manner
  • Ability to output to different types of consumers and systems
  • Hands-on experience with Linux and Windows operating systems and their associated development platforms

10. BS in Computer Science with 8 years of Experience

  • Experience developing advanced ML models for forecasting, scoring, etc., driving decisions in more than one corporate functional area, such as Sales, Finance, Support, etc.
  • Experience in data science or machine learning
  • Proven ability to apply scientific methods to solve real-world problems
  • Experience with Machine Learning techniques, e.g., classification, clustering, regularization, optimization, dimension reduction, etc.
  • Experience with SQL and Python
  • Hands-on experience in pulling data from external sources using APIs, joining data from disparate data systems and distilling large data sets into actionable insights that drive business value
  • Experience with data marts, data mining and data warehousing
  • Strong data analysis and scientific thinking skills
  • Proficient in data exploration and visualization tools such as Tableau
  • Deep understanding of statistical analysis, regression and predictive modeling, data mining and data warehousing concepts
  • Proficient in writing complex structured query language (SQL) queries on large datasets and relational databases for data manipulation and analysis
  • Experience working with Hadoop, SQL Server, Snowflake and enterprise solutions like Salesforce.com, Eloqua, Mixpanel and Optimizely
  • Demonstrated ability to work on cross-functional projects

11. BS in Machine Learning with 6 years of Experience

  • Experience building predictive models in a commercial environment, ideally GBMs (experience with XGBoost or LightGB)
  • Strong technical experience using SQL, Python or R
  • Experience solving commercial problems and generating insights from large customer or transactional data sets
  • Experience delivering analytical solutions in either a consulting or end-user business
  • Data Science experience within Supply Chain, Mining or Logistics experience
  • Strong commercial acumen and problem-solving skillset
  • Ability to work with and positively influence a variety of people across all levels and functions 
  • Exceptional communication, partnership and collaboration skills
  • Comfortable with juggling multiple projects and deadlines
  • Experience in NLP and Language models 
  • Deep understanding of customer service organizations, including contact centers and related KPIs and technology (e.g., speech analytics, call routing, workforce management, process automation, chatbots, etc.) 

12. BS in Business Analytics with 5 years of Experience

  • Significant experience in applying a range of data science and machine learning techniques to deliver business value
  • Ability to benchmark and prioritise the possible impact of data science projects, drawing on a wide range of previous experiences to give a sense of the potential
  • Advanced proficiency in at least two of SQL/R/Python/similar programming languages
  • Experience using BI Tools such as Power BI to set up dashboards with an emphasis on providing value to the business
  • Experience in leading a team of data scientists, with the ability to develop both the technical capabilities and softer skills of an individual
  • Experience managing the data science project lifecycle
  • Credibility with stakeholders at all levels of the business
  • Able to expertly convert complex data and analysis into concise and easy-to-understand presentations and insights
  • Commercially astute analytics projects that support strategic decision-making

13. BS in Computer Science with 8 years of Experience

  • Expertise in at least one technical domain (e.g., machine learning, simulation, optimisation, forecasting, NLP, econometrics, etc.)
  • Experience with different programming languages and a high level of capability in at least one language - Python, Scala, Java, or similar
  • Understanding of common data structures and algorithms
  • Understanding of time and space complexity
  • Experience in leading Data Science project developments involving multiple stakeholders
  • Experience of delivering high-impact Data Science developments within complex organisations
  • Experience of partnering with technology teams to productionize developments and roll out at scale
  • Demonstrated ability and desire to continually expand skill set, and learn from and teach others
  • Keen attention to detail with the ability to effectively prioritize and execute multiple tasks
  • Experience in the telecommunications industry, or two other consumer-based industries
  • Working knowledge of current industry best practices for online experimentation
  • Experience with Hadoop, particularly HIVE and Spark
  • Knowledge of other relevant tools such as SAS, SPSS, Alteryx, and Linux
  • Familiarity with the open-source ecosystems surrounding R (CRAN), Python (PyPi), and/or Hadoop

14. BS in Electrical Engineering with 4 years of Experience

  • Intermediate to advanced Python skills
  • Experience with at least one Deep Learning framework such as PyTorch or TensorFlow/Keras
  • Expert understanding of ML best practices
  • Solid understanding of ML/DL methods and architectures and mastery of performance assessment
  • Demonstrated ability to develop novel machine learning methods that go beyond putting together existing code, and to apply problem-solving skills to complex issues
  • Excellent written and verbal communication skills
  • Ability to work autonomously and collaboratively as part of a team to both teach and learn every day
  • Continuously looking for opportunities to learn, build skills and share learning
  • Proficiency in Linux environment (including shell scripting), experience with database languages (e.g., SQL, No-SQL)
  • Experience with version control practices and tools (Git, Perforce, etc.)
  • Familiarity with cloud computing services (AWS, GCP, or Azure)

15. BA in Anthropology with 3 years of Experience

  • Experience in data analysis or a related field
  • Experience with statistical and machine learning algorithms for predictive modeling, including real-time analysis of telemetry data
  • Expert SQL skills and experience with relational databases
  • Experience with non-relational databases
  • Programming experience with Python and one or more analytics development platforms, such as R, SAS, Scala, Java, Julia
  • Familiarity with BI reporting tools (such as Tableau, Qlik Sense, Power BI)
  • Experience in data analysis and predictive modeling using time series data
  • Familiarity with cloud-based data and analytics platforms (such as Azure, AWS, Google)

16. BS in Cognitive Science with 5 years of Experience

  • Experience in Data Science
  • Interested in building relationships and increasing the adoption of data science across the business
  • Excellent analytical problem-solving capabilities coupled with a willingness to learn
  • Ability to tell compelling stories from the data
  • Prior experience with influencing drug discovery or biopharmaceutical project teams
  • Experience with the analysis and interpretation of high-throughput immunology datasets, such as single-cell RNA-seq, TCR-seq, CITE-seq, mass cytometry, or high-dimensional flow cytometry
  • Strong analytical thinking, scientific rigor, and publication record
  • Demonstrated business acumen, people and project leadership competencies, and technical expertise
  • Excellent communication competencies to include presentations of quantitative analyses in a clear, concise, and actionable manner to key stakeholders across multiple functions
  • Ability to communicate with senior stakeholders and work in complex organisations
  • Experience with open-source ML libraries and technologies, specifically Python

17. BS in Statistics with 6 years of Experience

  • Experience applying analytics skills to drive projects that have had a proven impact on strategic decisions
  • Strong ability to communicate
  • Explaining complex concepts to diverse audiences and crafting compelling stories
  • Expertise in data manipulation and statistical programming languages (e.g., SQL, R, Python), and knowledge of cloud data environments (e.g., AWS)
  • Strength in one or more visualisation tools (Tableau, R-Shiny, etc.)
  • Understanding of the SaaS development, business model and metrics
  • Familiarity working with Product Management, Engineering, Design, Customer Research and Data Engineering teams
  • Must have a proven knowledge in the implementation of Machine Learning and clustering techniques
  • Strong commercial experience with Python and Visualisation and a proficient knowledge of R, AWS, and Scala
  • Previous commercial exposure to tools such as AZURE and AWS
  • Fluent in English with a good understanding of Dutch
  • Excellent communication skills and team and colleague engagement

18. BS in Mathematics with 4 years of Experience

  • Working experience in progressively complex 
  • Demonstrates proficiency in all areas of mathematical analysis methods, machine learning, statistical analyses, predictive modeling and advanced in-depth specialization in some areas
  • Strong skills to effectively communicate and negotiate across business and in the external healthcare environment
  • Excellent analytical and problem-solving skills
  • Strong organizational, management and leadership skills
  • Deep knowledge of advanced analytics tools and languages to analyze large data sets from multiple data sources
  • Solid understanding of the health care industry, products, and systems
  • Demonstrates a strong ability to communicate technical concepts and implications to business partners
  • Experience programming with Python
  • Experience in building machine learning models and deploying them into production

19. BS in Applied Mathematics with 7 years of Experience

  • Extensive experience in Python and SQL
  • Familiarity with visualization tools such as Tableau, Looker, or Power BI
  • Ability to effectively share technical information, communicate technical issues and solutions to all levels of business
  • Able to work independently and juggle multiple projects - can identify primary and secondary objectives, prioritize time and communicate timeline to team members
  • Ability and desire to take product/project ownership
  • Ability to think creatively, strategically and technically
  • Strong passion for answering complex business questions using structured problem-solving and rigorous data analysis
  • Excellent leadership, facilitation, and interpersonal skills, with the ability to work across functional lines and at many levels
  • Ability to think creatively, strategically and technically
  • Ability to work a flexible schedule based on department and Company needs
  • Experience working with data technologies that allow effective storage and analysis of large amounts of data (e.g., Spark, Presto, Hive, etc.)
  • Experience in time series forecasting methods

20. BS in Artificial Intelligence with 5 years of Experience

  • Strong problem-solving skills with an emphasis on product development
  • Experience using statistical computer languages (Pig, Python, SQL, etc.) to manipulate data and draw insights from large data sets
  • Experience with AWS
  • Knowledge of M/L 
  • Experience working with and creating data architectures
  • Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks
  • Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests, proper usage, etc.) and experience with applications
  • Excellent written and verbal communication skills for coordinating across teams
  • Experience manipulating data sets and building statistical models
  • Knowledge and experience in statistical and data mining techniques

21. BS in Electrical Engineering with 3 years of Experience

  • Proficiency in data/statistical analytical tools, such as SQL, R and Python
  • Strong industry experience in relevant data mining domains
  • Solid experience as being tech lead or DS manager
  • Tracking records of making successful mid/long-term technical strategic bets
  • Ability to think and communicate critically, rigorously, and concisely
  • Strong ownership, proactive and skillful communication
  • Ability to handle high complexity, urgency, cross-functional alignment while being consistently autonomic, objective and rational
  • Coding knowledge and experience with several languages such as C, Java, JavaScript, etc.

22. BA in Sociology with 4 years of Experience

  • Working experience in an international matrix organization
  • Experience in applying statistical solutions to business problems
  • Expert understanding of various data science methods
  • Working experience in scientific programming languages such as Python
  • Basic knowledge about non-relational database technology and distributed computing (Hadoop, Spark)
  • Knowledge of agile manifesto, values, principles and practices such as Kanban and Scrum
  • Experience in a data science leadership position
  • Advanced analytics and SQL skills
  • Advanced knowledge of statistics such as statistical power analysis, significance testing, and t-tests
  • Professional habits around model validation, testing, and tracking
  • Proven ability to translate business requirements into actionable data science projects and results

23. BS in Information Systems with 6 years of Experience

  • Basic understanding of SQL and/or Hive (or similar language) to perform ad hoc queries of large datasets
  • Basic understanding of relational and non-relational database systems
  • Basic understanding of cloud development platforms such as Azure or AWS and their associated data storage options
  • Good judgment, time management, and decision-making skills
  • Experience in Design Thinking or human-centered methods to identify and creatively solve customer needs, through a holistic understanding of the customer’s problem area
  • Hands-on experience with designing and maintaining CI/CD pipelines, including unit, integration and regression testing for development/production-ready code
  • Experience with Agile methodologies and have a track record of delivering products in a production environment
  • Experience with patents and publishing in research conferences/journals
  • Experience leading projects or small teams

24. BA in Economics with 7 years of Experience

  • Strong foundation in statistics and data analytics, expertise in survey research and statistical modeling
  • Experience working with large data sets to solve real-world business challenges
  • Experience managing teams to complete products within scope and on time
  • Proficiency in SQL and/or statistical packages (R, Python, STATA, etc)
  • Excellent interpersonal and communication skills
  • Demonstrated history of delivering high-quality analytic work to decision-makers in a client services or internal consulting/research environment
  • Experience with media science solutions and studies (media mix/optimization, attribution, etc.)
  • Familiarity with machine learning and causal inference
  • Experience working for a consulting, services, or advisory firm
  • Experience writing proposals, building cost and pricing estimates of proposed work, and selling the work to new or existing clients

25. BS in Cognitive Science with 5 years of Experience

  • Excellent understanding of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Decision Forests, etc.
  • Experience with common data science toolkits, such as R, Weka, NumPy, MATLAB, etc. 
  • Experience with data visualisation tools, such as D3.js, GGplot, etc.
  • Proficiency in using query languages such as SQL, Hive, Pig
  • Experience with NoSQL databases, such as MongoDB, Cassandra, and HBase
  • Good applied statistics skills, such as distributions, statistical testing, regression, etc.
  • Good scripting and programming skills
  • Experience working in a similar role
  • Demonstrable commercial experience in the application of machine learning techniques and statistical modelling
  • Experience using big data sets within cloud computing assets with AWS and Hadoop, i.e., Sagemaker
  • Experience working with SAS, SQL, Python, and R
  • Strong stakeholder management and communication skills

26. BS in Computational Science with 8 years of Experience

  • Experience with optimization and machine learning models design and implementation - can be in a marketing, operational or digital setting
  • Expertise in implementing next-gen models using machine learning in a Hadoop environment (e.g., kNN, MDP, neural networks, ensemble methods, NLP)
  • Excellent written and verbal communication skills
  • Ability to work and collaborate with internal and external partners
  • Must be able to think outside the box to implement creative solutions that solve business problems
  • Proven ability to work in a fast-paced environment, meet deadlines
  • Must be detail-oriented, organized, and perform at high standards
  • Experience in a data science role in at least one e-commerce or payments organisation
  • Leadership and management experience, as well as strong project management skills
  • Experience collaborating with partners to measure the impact of payments optimisation initiatives and presenting those findings in coherent recommendations
  • Proficiency with Python or similar programming languages and associated data science packages
  • Working knowledge of relational databases, including SQL, and large-scale distributed systems such as Hadoop and Spark
  • Experience with dashboard visualisation tools such as Tableau, Looker, Google Data Studio or similar

27. BS in Statistics with 6 years of Experience

  • Good understanding of data science principles and techniques, including advanced statistical techniques and concepts
  • Knowledge of machine learning techniques and their limitations within ‘real’ business processes
  • Strong problem-solving skills with a focus on product development
  • Ability to develop hypotheses and business cases for change, and to connect this to an analytical workplan
  • Excellent communication skills, with the ability to both support and challenge key stakeholders and delivery teams
  • Advanced analytical, statistical, and modelling skills using a range of coding languages and tools (R, Python, SQL, VBA, DataBricks)
  • Strong data visualisation skills using tools including Tableau and/or PowerBI
  • Exceptional ability to extract strategic insights from large data sets
  • Understand and translate the pattern recognition, exploration of the data
  • Extensive experience in statistical analysis, data mining and visualisation techniques
  • Experience applying machine learning methods with big data technologies
  • Experience in Python and the key analytical and machine learning libraries

28. BS in Artificial Intelligence with 5 years of Experience

  • Demonstrated technical/business experience in problem-framing and problem-solving with required project management skills
  • Experience in data analysis, modeling, and data mining
  • Strong experience with analytical software and technology (e.g., SAS, SAS Viya, R/Python, RStudio, R Shiny, AWS Data and Analytics services)
  • Experience with SQL, Hive, Presto, Hadoop, or other data querying languages
  • Experience designing and building statistical forecasting and machine learning models
  • Experience with communicating findings and actionable recommendations/insights to stakeholders using data visualization tools (e.g., Tableau, Power BI, etc.)
  • Exceptional customer service and collaboration skills
  • Demonstrated experience translating complex and technical subject matter
  • Ability to manage multiple and sometimes conflicting priorities

29. BS in Data Science with 7 years of Experience

  • Experience in building advanced Machine Learning models
  • Strong understanding of Python
  • Demonstrated familiarity with clinical concepts related to a broad range of clinical conditions and disease states
  • Experience with oncology, behavioral health and chronic conditions
  • Experience developing and validating machine learning models and tools
  • Experience with cloud-based ecosystems (GCP, AWS, Azure, Databricks)
  • Experience working in Agile environments
  • Experience working with EMR data
  • Excellent understanding and previous practical implementation of A/B testing and experiment design/frameworks
  • Experience or knowledge around MMM/Econometrics
  • Excellent ability to clearly communicate complex ideas
  • Excellent business judgement and strategic thinking, with the technical toolkit to enable delivery
  • Strong experience in collaborating and coordinating across multiple business departments

30. BS in Operations Research with 3 years of Experience

  • Work experience doing quantitative analysis in the tech industry
  • Ability to synthesize and communicate complex concepts and analyses in easy-to-understand ways
  • Strong track record of identifying key business questions, performing analyses, and communicating impactful findings in a clear and concise way
  • Solid grasp of common statistical methods and applications (A/B testing, probability, regression)
  • Expert experience in developing large and complex data pipelines using SQL
  • Familiar with Python or R
  • Experience with data visualization tools (e.g., Tableau)
  • Self-motivated, detail-oriented, continued curiosity, and highly organized

31. BS in Software Engineering with 8 years of Experience

  • Experience devising, developing and deploying data science/machine learning products in Production environments
  • Experience leading and supervising on/off-shore data science teams to support simultaneous business demands whilst meeting deadlines in a fast-paced, constantly changing environment
  • Solid experience of applying data-driven mathematical/statistical/Machine Learning models using R and Python, ideally in a financial services business environment
  • Strong knowledge of statistical modelling and Machine Learning concepts, including Econometric methods for time series forecasting
  • Professional experience working with database developers and data engineers to ensure the data points are optimally tuned for machine learning algorithms and data science applications
  • Solid experience using open source technologies (Linux, PostgreSQL, R, Python) to support predictive analytics activities and outputs
  • Proven ability to solve business problems, handle conflicts, anticipate issues/concerns, troubleshoot issues, and proactively institute creative solutions quickly and in detail
  • Exposure to MLOps (Machine Learning pipelines) in production
  • Exposure to distributed processing systems for big data workloads (Hadoop, Spark, AWS, Google Cloud Platform, Microsoft Azure)
  • Ability to establish strong working relationships with colleagues, other dependent functions and departments
  • Strong written and verbal communication, presentation, and technical writing skills
  • Familiarity with the Financial Services and Management Consulting industries

32. BS in Electrical Engineering with 4 years of Experience

  • Experience with a variety of neural networks such as CNN, RNN, ANN and LSTMs
  • Experience with applications of Machine Vision and Natural Language Processing
  • Highly effective at analyzing information, developing insights and brainstorming possible solutions
  • Highly experienced using common data analytics tools, data modeling, and data management (including labeling best practices)
  • Evidence of continued self-development (e.g., certifications in Coursera, Udacity, Google AI courses)
  • Expert in one or more common programming languages such as C++, Java, R, SQL, and Python
  • Familiar with turning algorithms into APIs
  • Must be able to learn from others and teach others, and to work collaboratively as part of a cross-functional team
  • Experience with Python and/or R, with some experience building or maintaining modular applications, pipelines, or libraries
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