Lead Data Scientist

2 weeks ago

Bangalore, Karnataka, India Hiret Full time

Preferred Qualifications:


- B.Tech/B.E/M.E/M.Tech/MSC in Data Science/Computer Science/Statistics/AI/ML or Minimum 8 years professional experience in the field of data science, ML or business intelligence.


- Bachelors degree in computer science, Math, Software Engineering, Computer Engineering, or related field AND 7+ years experience in business analytics, data science, software development, data modeling, or data engineering work


- OR masters degree in computer science, Math, Software Engineering, Computer Engineering, or related field AND 7+ years experience in business analytics, data science, software development, data modeling or data engineering work


- OR equivalent experience.


- AND querying with traditional database management system (MY SQL/ MONGO DB/MARIA DB)


Skills Required:


- The ideal candidate for this position must possess exceptional written and verbal communication skills, adept at engaging with cross-functional teams and articulating findings to both technical and non-technical audiences.


- They should exhibit proactive communication, challenging existing approaches and suggesting innovative machine learning techniques.


- Leadership qualities are essential, demonstrated through thought leadership, mentorship, and training of junior data scientists.


- This individual will lead analytical projects independently, engaging stakeholders effectively and utilizing strong communication skills to garner consensus on recommendations.


- The ability to thrive in a fast-paced environment, multitask, and meet deadlines is crucial.


- They should be self-motivated, detail-oriented, and proactive in identifying opportunities for improvement.


- Additionally, proficiency in presentation skills for conveying findings and recommendations to management and stakeholders, coupled with strong problem-solving and analytical abilities, is imperative for success in this role.


Location: Kudlugate, Bangalore


Position Type: Full Time


Role Type: Team Handler


Role Summary / Profile Summary:


We are looking for high-energy, creative modeling geeks who are willing to work in a dynamic environment to solve real life day to day problems, leveraging data science techniques. You will enjoy and be successful in this role if you are curious and willing to challenge the status quo and come up with data driven solutions to ambiguous problems.


As a Lead Data Scientist, you will work on huge amount of data to develop Machine Learning solutions and provide insights to team and customers to make data driven decision. Additionally, you will work closely with engineering teams, product managers, business leaders to build data pipelines, and bring intelligence to identify business problems, design analytical approaches, and provide actionable insights into automobile solutioning.


Roles and Responsibilities:


- Lead a team of data scientists and provide guidance and mentorship to ensure successful project delivery.


- Lead and manage projects, ensuring timely delivery and adherence to quality standards.


- Design and implement advanced data analysis techniques to extract meaningful insights from complex and large datasets.


- Develop and deploy machine learning models to solve business problems and optimize processes.


- Assess the effectiveness and accuracy of new data sources and data gathering techniques.


- Propose solutions and strategies to business challenges. Apply domain knowledge to understand business requirements and provide relevant solutions.


- Analyze large amounts of information to discover trends and patterns.


- Create data visualizations and reports to effectively communicate findings and recommendations to stakeholders.


- Ability to understand business concerns and formulate them as technical problems that can be solved using data and ML.


- Collaborate with cross-functional teams to identify opportunities for data-driven decision-making and develop strategies to leverage data assets.


- Stay updated with the latest advancements in data science, machine learning, and big data technologies to drive innovation within the organization.


- Assists with initial data collection and understands which analysis techniques appropriate and which tools are necessary for data exploration.


- Develops a foundational understanding of methodology and standard statistical options to analyze and organize data as required.


- Work with large, complex data sets, solving difficult, non-routine analysis problems with advanced data science methods.


- Applies (or develops if necessary) tools and pipelines to efficiently collect, clean, and prepare massive volumes of data for analysis.


- Transforms problems into analysis plans for data telemetry, metrics, predictive modeling, reporting, and experimentation.


- Communicates and gets alignment on analytics priorities.


- Work across engineering and product teams to enable metrics for product success.


- Understands modeling techniques used within the team, then run model tools on prepared data sets.


- Supports identification of dependencies, and the development of design documents for a product feature with oversight.


- Create and implement code for a product, service, or feature reusing code as applicable.


Technical Skills Required:


- Strong grasp of Statistics, Mathematical concepts, and algorithms.


- Experience using statistical concepts using StatsModel, scipy numpy


- Must be proficient in SQL to manipulate data and draw insights from typically MySQL/MS SQL Server or large data sets typically from tools like Big Query.


- Must be proficient in Python and have implemented many Classical machine Learning projects.


- Must be comfortable with Deep learning, Neural Network, Experience with Python libraries such as Pandas, NumPy, SciPy, Scikit-Learn


- Experience in knowledge of OOPS principles and programming


- Experience with variety of machine learning techniques (logistic regression, linear regression, lasso regression, k-means, random forest, XG boost, KNN, SVM, clustering, decision tree, and neural networks.


- Must have deployed multiple ML models.


- Knowledge of Source Control management tools like GIT, CVS, VSS, Subversion etc.


- Expertise with Microsoft Office products; including Excel, PowerPoint, Word.


- Knowledge of Data Structures, relational data, and big data platforms.


- Experience using business intelligence tools (e.g., Tableau, Google Data Studio, Power BI) and data frameworks (e.g., Deep understanding of a specific domain (e.g., Automotive, finance, healthcare, e-commerce) and the ability to apply domain knowledge to data analysis.


- Understand Transformers, and Large Language Models


- Has implemented and deployed models using Azure/Google/Amazon


- Machine Learning Operations


- Large Language Model Operations


- Has implemented many Deep Learning models using CNN/RNN Family

(ref:hirist.tech)

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